Overview

Dataset statistics

Number of variables29
Number of observations131
Missing cells183
Missing cells (%)4.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.8 KiB
Average record size in memory233.0 B

Variable types

Numeric9
Categorical20

Alerts

airdate has constant value "2020-12-25" Constant
url has a high cardinality: 131 distinct values High cardinality
name has a high cardinality: 116 distinct values High cardinality
image has a high cardinality: 52 distinct values High cardinality
_embedded_show_url has a high cardinality: 76 distinct values High cardinality
_embedded_show_name has a high cardinality: 76 distinct values High cardinality
_embedded_show_premiered has a high cardinality: 58 distinct values High cardinality
_embedded_show_officialSite has a high cardinality: 66 distinct values High cardinality
_embedded_show_summary has a high cardinality: 69 distinct values High cardinality
_links_self_href has a high cardinality: 131 distinct values High cardinality
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
season is highly correlated with numberHigh correlation
number is highly correlated with seasonHigh correlation
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
runtime is highly correlated with _embedded_show_runtime and 1 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with runtime and 1 other fieldsHigh correlation
_embedded_show_officialSite is highly correlated with _embedded_show_ended and 14 other fieldsHigh correlation
_embedded_show_ended is highly correlated with _embedded_show_officialSite and 9 other fieldsHigh correlation
_embedded_show_name is highly correlated with _embedded_show_officialSite and 14 other fieldsHigh correlation
summary is highly correlated with airdate and 1 other fieldsHigh correlation
_embedded_show_summary is highly correlated with _embedded_show_officialSite and 14 other fieldsHigh correlation
_embedded_show_genres is highly correlated with _embedded_show_officialSite and 8 other fieldsHigh correlation
type is highly correlated with _embedded_show_officialSite and 6 other fieldsHigh correlation
_embedded_show_type is highly correlated with _embedded_show_officialSite and 6 other fieldsHigh correlation
airdate is highly correlated with _embedded_show_officialSite and 15 other fieldsHigh correlation
airtime is highly correlated with _embedded_show_officialSite and 7 other fieldsHigh correlation
_embedded_show_status is highly correlated with _embedded_show_officialSite and 9 other fieldsHigh correlation
_embedded_show_premiered is highly correlated with _embedded_show_officialSite and 12 other fieldsHigh correlation
image is highly correlated with _embedded_show_officialSite and 15 other fieldsHigh correlation
_embedded_show_url is highly correlated with _embedded_show_officialSite and 14 other fieldsHigh correlation
_embedded_show_language is highly correlated with _embedded_show_officialSite and 7 other fieldsHigh correlation
_embedded_show_dvdCountry is highly correlated with _embedded_show_officialSite and 6 other fieldsHigh correlation
airstamp is highly correlated with _embedded_show_officialSite and 8 other fieldsHigh correlation
id is highly correlated with season and 17 other fieldsHigh correlation
season is highly correlated with id and 7 other fieldsHigh correlation
number is highly correlated with season and 7 other fieldsHigh correlation
type is highly correlated with id and 8 other fieldsHigh correlation
airtime is highly correlated with airstamp and 13 other fieldsHigh correlation
airstamp is highly correlated with id and 18 other fieldsHigh correlation
runtime is highly correlated with id and 14 other fieldsHigh correlation
image is highly correlated with id and 21 other fieldsHigh correlation
summary is highly correlated with runtime and 5 other fieldsHigh correlation
_embedded_show_id is highly correlated with id and 16 other fieldsHigh correlation
_embedded_show_url is highly correlated with id and 22 other fieldsHigh correlation
_embedded_show_name is highly correlated with id and 22 other fieldsHigh correlation
_embedded_show_type is highly correlated with id and 16 other fieldsHigh correlation
_embedded_show_language is highly correlated with id and 18 other fieldsHigh correlation
_embedded_show_genres is highly correlated with id and 20 other fieldsHigh correlation
_embedded_show_status is highly correlated with id and 16 other fieldsHigh correlation
_embedded_show_runtime is highly correlated with type and 17 other fieldsHigh correlation
_embedded_show_averageRuntime is highly correlated with id and 17 other fieldsHigh correlation
_embedded_show_premiered is highly correlated with id and 21 other fieldsHigh correlation
_embedded_show_ended is highly correlated with airtime and 15 other fieldsHigh correlation
_embedded_show_officialSite is highly correlated with id and 22 other fieldsHigh correlation
_embedded_show_weight is highly correlated with id and 17 other fieldsHigh correlation
_embedded_show_dvdCountry is highly correlated with image and 5 other fieldsHigh correlation
_embedded_show_summary is highly correlated with id and 22 other fieldsHigh correlation
_embedded_show_updated is highly correlated with id and 17 other fieldsHigh correlation
number has 7 (5.3%) missing values Missing
runtime has 19 (14.5%) missing values Missing
image has 79 (60.3%) missing values Missing
_embedded_show_runtime has 61 (46.6%) missing values Missing
_embedded_show_averageRuntime has 17 (13.0%) missing values Missing
url is uniformly distributed Uniform
name is uniformly distributed Uniform
image is uniformly distributed Uniform
_links_self_href is uniformly distributed Uniform
id has unique values Unique
url has unique values Unique
_links_self_href has unique values Unique
_embedded_show_weight has 5 (3.8%) zeros Zeros

Reproduction

Analysis started2022-05-10 02:20:40.561658
Analysis finished2022-05-10 02:21:20.352362
Duration39.79 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct131
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2055166.145
Minimum1910449
Maximum2324417
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:21:20.430229image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1910449
5-th percentile1950007.5
Q11981794.5
median1993101
Q32126990
95-th percentile2292864.5
Maximum2324417
Range413968
Interquartile range (IQR)145195.5

Descriptive statistics

Standard deviation117931.4368
Coefficient of variation (CV)0.05738292112
Kurtosis-0.245962206
Mean2055166.145
Median Absolute Deviation (MAD)20526
Skewness1.153188784
Sum269226765
Variance1.390782378 × 1010
MonotonicityNot monotonic
2022-05-09T21:21:20.526555image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19681151
 
0.8%
22404561
 
0.8%
21972911
 
0.8%
20946671
 
0.8%
20741881
 
0.8%
20722281
 
0.8%
20519851
 
0.8%
20000691
 
0.8%
20000681
 
0.8%
19975291
 
0.8%
Other values (121)121
92.4%
ValueCountFrequency (%)
19104491
0.8%
19248911
0.8%
19500031
0.8%
19500041
0.8%
19500051
0.8%
19500061
0.8%
19500071
0.8%
19500081
0.8%
19500091
0.8%
19504051
0.8%
ValueCountFrequency (%)
23244171
0.8%
23244161
0.8%
23237951
0.8%
23237941
0.8%
23237931
0.8%
22928661
0.8%
22928651
0.8%
22928641
0.8%
22928631
0.8%
22928621
0.8%

url
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct131
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
https://www.tvmaze.com/episodes/1968115/po-sezonu-videodajdzest-seasonvar-6x52-vypusk-306
 
1
https://www.tvmaze.com/episodes/2240456/filly-funtasia-2x02-the-treasure-hunt
 
1
https://www.tvmaze.com/episodes/2197291/struggle-meals-1x15-show-me-the-mole
 
1
https://www.tvmaze.com/episodes/2094667/paradka-1x01-smagcausie-obstoatelstva
 
1
https://www.tvmaze.com/episodes/2074188/my-lecturer-my-husband-1x03-episode-3
 
1
Other values (126)
126 

Length

Max length171
Median length96
Mean length76.79389313
Min length58

Characters and Unicode

Total characters10060
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique131 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/1968115/po-sezonu-videodajdzest-seasonvar-6x52-vypusk-306
2nd rowhttps://www.tvmaze.com/episodes/2121269/fiksiki-4x18-sanki
3rd rowhttps://www.tvmaze.com/episodes/1984017/roast-battle-labelcom-1x15-15-dana-milohin
4th rowhttps://www.tvmaze.com/episodes/1991483/psih-s01-special-film-o-filme
5th rowhttps://www.tvmaze.com/episodes/1988016/muzskaa-tema-1x05-seria-5

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1968115/po-sezonu-videodajdzest-seasonvar-6x52-vypusk-3061
 
0.8%
https://www.tvmaze.com/episodes/2240456/filly-funtasia-2x02-the-treasure-hunt1
 
0.8%
https://www.tvmaze.com/episodes/2197291/struggle-meals-1x15-show-me-the-mole1
 
0.8%
https://www.tvmaze.com/episodes/2094667/paradka-1x01-smagcausie-obstoatelstva1
 
0.8%
https://www.tvmaze.com/episodes/2074188/my-lecturer-my-husband-1x03-episode-31
 
0.8%
https://www.tvmaze.com/episodes/2072228/top-dog-fighting-championship-6x01-mihail-sivyj-vs-andrej-panda1
 
0.8%
https://www.tvmaze.com/episodes/2051985/pro-balet-s-nikolaem-ciskaridze-1x31-nikolaj-ciskaridze-pro-balet-vypusk30-golubaa-ptica-russkaa-versia-pro-ballet-part30-sleepingb1
 
0.8%
https://www.tvmaze.com/episodes/2000069/ultimate-note-1x22-episode-221
 
0.8%
https://www.tvmaze.com/episodes/2000068/ultimate-note-1x21-episode-211
 
0.8%
https://www.tvmaze.com/episodes/1997529/the-penalty-zone-1x22-episode-221
 
0.8%
Other values (121)121
92.4%

Length

2022-05-09T21:21:20.652790image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/1968115/po-sezonu-videodajdzest-seasonvar-6x52-vypusk-3061
 
0.8%
https://www.tvmaze.com/episodes/1976541/var-tid-ar-nu-4x02-midsommar1
 
0.8%
https://www.tvmaze.com/episodes/1984017/roast-battle-labelcom-1x15-15-dana-milohin1
 
0.8%
https://www.tvmaze.com/episodes/1991483/psih-s01-special-film-o-filme1
 
0.8%
https://www.tvmaze.com/episodes/1988016/muzskaa-tema-1x05-seria-51
 
0.8%
https://www.tvmaze.com/episodes/2062929/god-of-ten-thousand-realms-1x04-episode-41
 
0.8%
https://www.tvmaze.com/episodes/2030154/fox-spirit-matchmaker-9x04-episode-1251
 
0.8%
https://www.tvmaze.com/episodes/2324416/unique-lady-2x07-episode-71
 
0.8%
https://www.tvmaze.com/episodes/2324417/unique-lady-2x08-episode-81
 
0.8%
https://www.tvmaze.com/episodes/1972575/the-wolf-1x33-episode-331
 
0.8%
Other values (121)121
92.4%

Most occurring characters

ValueCountFrequency (%)
e816
 
8.1%
-718
 
7.1%
/655
 
6.5%
t640
 
6.4%
s629
 
6.3%
o530
 
5.3%
a433
 
4.3%
w430
 
4.3%
i404
 
4.0%
m382
 
3.8%
Other values (30)4423
44.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6896
68.5%
Decimal Number1398
 
13.9%
Other Punctuation1048
 
10.4%
Dash Punctuation718
 
7.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e816
11.8%
t640
 
9.3%
s629
 
9.1%
o530
 
7.7%
a433
 
6.3%
w430
 
6.2%
i404
 
5.9%
m382
 
5.5%
p368
 
5.3%
d271
 
3.9%
Other values (16)1993
28.9%
Decimal Number
ValueCountFrequency (%)
1271
19.4%
2205
14.7%
0201
14.4%
9159
11.4%
4120
8.6%
894
 
6.7%
589
 
6.4%
689
 
6.4%
387
 
6.2%
783
 
5.9%
Other Punctuation
ValueCountFrequency (%)
/655
62.5%
.262
 
25.0%
:131
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-718
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin6896
68.5%
Common3164
31.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e816
11.8%
t640
 
9.3%
s629
 
9.1%
o530
 
7.7%
a433
 
6.3%
w430
 
6.2%
i404
 
5.9%
m382
 
5.5%
p368
 
5.3%
d271
 
3.9%
Other values (16)1993
28.9%
Common
ValueCountFrequency (%)
-718
22.7%
/655
20.7%
1271
 
8.6%
.262
 
8.3%
2205
 
6.5%
0201
 
6.4%
9159
 
5.0%
:131
 
4.1%
4120
 
3.8%
894
 
3.0%
Other values (4)348
11.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII10060
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e816
 
8.1%
-718
 
7.1%
/655
 
6.5%
t640
 
6.4%
s629
 
6.3%
o530
 
5.3%
a433
 
4.3%
w430
 
4.3%
i404
 
4.0%
m382
 
3.8%
Other values (30)4423
44.0%

name
Categorical

HIGH CARDINALITY
UNIFORM

Distinct116
Distinct (%)88.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Episode 6
 
4
Episode 7
 
4
Episode 8
 
3
Episode 4
 
3
Episode 1
 
2
Other values (111)
115 

Length

Max length96
Median length31
Mean length15.48091603
Min length3

Characters and Unicode

Total characters2028
Distinct characters125
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)81.7%

Sample

1st rowВыпуск 306
2nd rowСанки
3rd row#15 - Даня Милохин
4th rowФильм о фильме
5th rowСерия 5

Common Values

ValueCountFrequency (%)
Episode 64
 
3.1%
Episode 74
 
3.1%
Episode 83
 
2.3%
Episode 43
 
2.3%
Episode 12
 
1.5%
Episode 222
 
1.5%
Episode 32
 
1.5%
Episode 232
 
1.5%
Episode 212
 
1.5%
Vera - Mudanças1
 
0.8%
Other values (106)106
80.9%

Length

2022-05-09T21:21:20.778033image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
episode38
 
10.7%
the16
 
4.5%
of10
 
2.8%
65
 
1.4%
i5
 
1.4%
and5
 
1.4%
74
 
1.1%
24
 
1.1%
a4
 
1.1%
34
 
1.1%
Other values (233)260
73.2%

Most occurring characters

ValueCountFrequency (%)
224
 
11.0%
e175
 
8.6%
o121
 
6.0%
s106
 
5.2%
i105
 
5.2%
a90
 
4.4%
r83
 
4.1%
t69
 
3.4%
d62
 
3.1%
p59
 
2.9%
Other values (115)934
46.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1376
67.9%
Uppercase Letter300
 
14.8%
Space Separator224
 
11.0%
Decimal Number86
 
4.2%
Other Punctuation23
 
1.1%
Dash Punctuation15
 
0.7%
Other Letter2
 
0.1%
Open Punctuation1
 
< 0.1%
Close Punctuation1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e175
 
12.7%
o121
 
8.8%
s106
 
7.7%
i105
 
7.6%
a90
 
6.5%
r83
 
6.0%
t69
 
5.0%
d62
 
4.5%
p59
 
4.3%
n58
 
4.2%
Other values (48)448
32.6%
Uppercase Letter
ValueCountFrequency (%)
E44
14.7%
A25
 
8.3%
T24
 
8.0%
M18
 
6.0%
S17
 
5.7%
B17
 
5.7%
H14
 
4.7%
D13
 
4.3%
W11
 
3.7%
F11
 
3.7%
Other values (32)106
35.3%
Decimal Number
ValueCountFrequency (%)
217
19.8%
115
17.4%
313
15.1%
67
8.1%
47
8.1%
77
8.1%
86
 
7.0%
56
 
7.0%
06
 
7.0%
92
 
2.3%
Other Punctuation
ValueCountFrequency (%)
.4
17.4%
,4
17.4%
?3
13.0%
:3
13.0%
#3
13.0%
'2
8.7%
&2
8.7%
/1
 
4.3%
!1
 
4.3%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
224
100.0%
Dash Punctuation
ValueCountFrequency (%)
-15
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1505
74.2%
Common350
 
17.3%
Cyrillic171
 
8.4%
Han2
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e175
 
11.6%
o121
 
8.0%
s106
 
7.0%
i105
 
7.0%
a90
 
6.0%
r83
 
5.5%
t69
 
4.6%
d62
 
4.1%
p59
 
3.9%
n58
 
3.9%
Other values (42)577
38.3%
Cyrillic
ValueCountFrequency (%)
и16
 
9.4%
а16
 
9.4%
с10
 
5.8%
е8
 
4.7%
л7
 
4.1%
р7
 
4.1%
к7
 
4.1%
в6
 
3.5%
о6
 
3.5%
я6
 
3.5%
Other values (38)82
48.0%
Common
ValueCountFrequency (%)
224
64.0%
217
 
4.9%
115
 
4.3%
-15
 
4.3%
313
 
3.7%
67
 
2.0%
47
 
2.0%
77
 
2.0%
86
 
1.7%
56
 
1.7%
Other values (13)33
 
9.4%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1846
91.0%
Cyrillic171
 
8.4%
None9
 
0.4%
CJK2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
224
 
12.1%
e175
 
9.5%
o121
 
6.6%
s106
 
5.7%
i105
 
5.7%
a90
 
4.9%
r83
 
4.5%
t69
 
3.7%
d62
 
3.4%
p59
 
3.2%
Other values (60)752
40.7%
Cyrillic
ValueCountFrequency (%)
и16
 
9.4%
а16
 
9.4%
с10
 
5.8%
е8
 
4.7%
л7
 
4.1%
р7
 
4.1%
к7
 
4.1%
в6
 
3.5%
о6
 
3.5%
я6
 
3.5%
Other values (38)82
48.0%
None
ValueCountFrequency (%)
ø3
33.3%
ö2
22.2%
å2
22.2%
ç1
 
11.1%
ó1
 
11.1%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

season
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct10
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.79389313
Minimum1
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:21:20.872627image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile9
Maximum2020
Range2019
Interquartile range (IQR)1

Descriptive statistics

Standard deviation176.3016522
Coefficient of variation (CV)9.907986461
Kurtosis130.9317331
Mean17.79389313
Median Absolute Deviation (MAD)0
Skewness11.44109677
Sum2331
Variance31082.27258
MonotonicityNot monotonic
2022-05-09T21:21:20.951177image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
175
57.3%
227
 
20.6%
410
 
7.6%
98
 
6.1%
34
 
3.1%
63
 
2.3%
51
 
0.8%
171
 
0.8%
20201
 
0.8%
181
 
0.8%
ValueCountFrequency (%)
175
57.3%
227
 
20.6%
34
 
3.1%
410
 
7.6%
51
 
0.8%
63
 
2.3%
98
 
6.1%
171
 
0.8%
181
 
0.8%
20201
 
0.8%
ValueCountFrequency (%)
20201
 
0.8%
181
 
0.8%
171
 
0.8%
98
 
6.1%
63
 
2.3%
51
 
0.8%
410
 
7.6%
34
 
3.1%
227
 
20.6%
175
57.3%

number
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct31
Distinct (%)25.0%
Missing7
Missing (%)5.3%
Infinite0
Infinite (%)0.0%
Mean12.68548387
Minimum1
Maximum352
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:21:21.070951image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q311.25
95-th percentile33
Maximum352
Range351
Interquartile range (IQR)8.25

Descriptive statistics

Standard deviation33.18986204
Coefficient of variation (CV)2.616365475
Kurtosis90.52177946
Mean12.68548387
Median Absolute Deviation (MAD)3
Skewness8.986459044
Sum1573
Variance1101.566942
MonotonicityNot monotonic
2022-05-09T21:21:21.163944image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
413
 
9.9%
612
 
9.2%
112
 
9.2%
511
 
8.4%
211
 
8.4%
710
 
7.6%
39
 
6.9%
87
 
5.3%
103
 
2.3%
153
 
2.3%
Other values (21)33
25.2%
(Missing)7
 
5.3%
ValueCountFrequency (%)
112
9.2%
211
8.4%
39
6.9%
413
9.9%
511
8.4%
612
9.2%
710
7.6%
87
5.3%
93
 
2.3%
103
 
2.3%
ValueCountFrequency (%)
3521
 
0.8%
871
 
0.8%
741
 
0.8%
521
 
0.8%
351
 
0.8%
341
 
0.8%
332
1.5%
311
 
0.8%
241
 
0.8%
233
2.3%

type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
regular
124 
insignificant_special
 
4
significant_special
 
3

Length

Max length21
Median length7
Mean length7.702290076
Min length7

Characters and Unicode

Total characters1009
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowinsignificant_special
5th rowregular

Common Values

ValueCountFrequency (%)
regular124
94.7%
insignificant_special4
 
3.1%
significant_special3
 
2.3%

Length

2022-05-09T21:21:21.256851image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:21:21.350912image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
regular124
94.7%
insignificant_special4
 
3.1%
significant_special3
 
2.3%

Most occurring characters

ValueCountFrequency (%)
r248
24.6%
a138
13.7%
e131
13.0%
g131
13.0%
l131
13.0%
u124
12.3%
i32
 
3.2%
n18
 
1.8%
s14
 
1.4%
c14
 
1.4%
Other values (4)28
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1002
99.3%
Connector Punctuation7
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r248
24.8%
a138
13.8%
e131
13.1%
g131
13.1%
l131
13.1%
u124
12.4%
i32
 
3.2%
n18
 
1.8%
s14
 
1.4%
c14
 
1.4%
Other values (3)21
 
2.1%
Connector Punctuation
ValueCountFrequency (%)
_7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1002
99.3%
Common7
 
0.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
r248
24.8%
a138
13.8%
e131
13.1%
g131
13.1%
l131
13.1%
u124
12.4%
i32
 
3.2%
n18
 
1.8%
s14
 
1.4%
c14
 
1.4%
Other values (3)21
 
2.1%
Common
ValueCountFrequency (%)
_7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1009
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r248
24.6%
a138
13.7%
e131
13.0%
g131
13.0%
l131
13.0%
u124
12.3%
i32
 
3.2%
n18
 
1.8%
s14
 
1.4%
c14
 
1.4%
Other values (4)28
 
2.8%

airdate
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2020-12-25
131 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1310
Distinct characters5
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-25
2nd row2020-12-25
3rd row2020-12-25
4th row2020-12-25
5th row2020-12-25

Common Values

ValueCountFrequency (%)
2020-12-25131
100.0%

Length

2022-05-09T21:21:21.449620image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:21:21.548675image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-25131
100.0%

Most occurring characters

ValueCountFrequency (%)
2524
40.0%
0262
20.0%
-262
20.0%
1131
 
10.0%
5131
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1048
80.0%
Dash Punctuation262
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2524
50.0%
0262
25.0%
1131
 
12.5%
5131
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-262
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1310
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2524
40.0%
0262
20.0%
-262
20.0%
1131
 
10.0%
5131
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1310
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2524
40.0%
0262
20.0%
-262
20.0%
1131
 
10.0%
5131
 
10.0%

airtime
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct11
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
nan
98 
20:00
11 
12:00
 
7
06:00
 
7
21:00
 
2
Other values (6)
 
6

Length

Max length5
Median length3
Mean length3.503816794
Min length3

Characters and Unicode

Total characters459
Distinct characters11
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)4.6%

Sample

1st rownan
2nd rownan
3rd rownan
4th row12:00
5th row12:00

Common Values

ValueCountFrequency (%)
nan98
74.8%
20:0011
 
8.4%
12:007
 
5.3%
06:007
 
5.3%
21:002
 
1.5%
10:001
 
0.8%
17:001
 
0.8%
19:001
 
0.8%
20:451
 
0.8%
22:001
 
0.8%

Length

2022-05-09T21:21:21.611449image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan98
74.8%
20:0011
 
8.4%
12:007
 
5.3%
06:007
 
5.3%
21:002
 
1.5%
10:001
 
0.8%
17:001
 
0.8%
19:001
 
0.8%
20:451
 
0.8%
22:001
 
0.8%

Most occurring characters

ValueCountFrequency (%)
n196
42.7%
a98
21.4%
086
18.7%
:33
 
7.2%
223
 
5.0%
112
 
2.6%
67
 
1.5%
71
 
0.2%
91
 
0.2%
41
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter294
64.1%
Decimal Number132
28.8%
Other Punctuation33
 
7.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
086
65.2%
223
 
17.4%
112
 
9.1%
67
 
5.3%
71
 
0.8%
91
 
0.8%
41
 
0.8%
51
 
0.8%
Lowercase Letter
ValueCountFrequency (%)
n196
66.7%
a98
33.3%
Other Punctuation
ValueCountFrequency (%)
:33
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin294
64.1%
Common165
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
086
52.1%
:33
 
20.0%
223
 
13.9%
112
 
7.3%
67
 
4.2%
71
 
0.6%
91
 
0.6%
41
 
0.6%
51
 
0.6%
Latin
ValueCountFrequency (%)
n196
66.7%
a98
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII459
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n196
42.7%
a98
21.4%
086
18.7%
:33
 
7.2%
223
 
5.0%
112
 
2.6%
67
 
1.5%
71
 
0.2%
91
 
0.2%
41
 
0.2%

airstamp
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct15
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2020-12-25T12:00:00+00:00
75 
2020-12-25T04:00:00+00:00
14 
2020-12-25T11:00:00+00:00
13 
2020-12-25T05:00:00+00:00
 
7
2020-12-25T16:00:00+00:00
 
7
Other values (10)
15 

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters3275
Distinct characters14
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)6.1%

Sample

1st row2020-12-25T00:00:00+00:00
2nd row2020-12-25T00:00:00+00:00
3rd row2020-12-25T00:00:00+00:00
4th row2020-12-25T00:00:00+00:00
5th row2020-12-25T00:00:00+00:00

Common Values

ValueCountFrequency (%)
2020-12-25T12:00:00+00:0075
57.3%
2020-12-25T04:00:00+00:0014
 
10.7%
2020-12-25T11:00:00+00:0013
 
9.9%
2020-12-25T05:00:00+00:007
 
5.3%
2020-12-25T16:00:00+00:007
 
5.3%
2020-12-25T00:00:00+00:005
 
3.8%
2020-12-25T13:00:00+00:002
 
1.5%
2020-12-25T02:00:00+00:001
 
0.8%
2020-12-25T06:30:00+00:001
 
0.8%
2020-12-25T07:00:00+00:001
 
0.8%
Other values (5)5
 
3.8%

Length

2022-05-09T21:21:21.705678image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-25t12:00:00+00:0075
57.3%
2020-12-25t04:00:00+00:0014
 
10.7%
2020-12-25t11:00:00+00:0013
 
9.9%
2020-12-25t05:00:00+00:007
 
5.3%
2020-12-25t16:00:00+00:007
 
5.3%
2020-12-25t00:00:00+00:005
 
3.8%
2020-12-25t13:00:00+00:002
 
1.5%
2020-12-25t02:00:00+00:001
 
0.8%
2020-12-25t06:30:00+00:001
 
0.8%
2020-12-25t07:00:00+00:001
 
0.8%
Other values (5)5
 
3.8%

Most occurring characters

ValueCountFrequency (%)
01344
41.0%
2601
18.4%
:393
 
12.0%
-262
 
8.0%
1244
 
7.5%
5140
 
4.3%
T131
 
4.0%
+131
 
4.0%
415
 
0.5%
68
 
0.2%
Other values (4)6
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2358
72.0%
Other Punctuation393
 
12.0%
Dash Punctuation262
 
8.0%
Uppercase Letter131
 
4.0%
Math Symbol131
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
01344
57.0%
2601
25.5%
1244
 
10.3%
5140
 
5.9%
415
 
0.6%
68
 
0.3%
33
 
0.1%
71
 
< 0.1%
81
 
< 0.1%
91
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
:393
100.0%
Dash Punctuation
ValueCountFrequency (%)
-262
100.0%
Uppercase Letter
ValueCountFrequency (%)
T131
100.0%
Math Symbol
ValueCountFrequency (%)
+131
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common3144
96.0%
Latin131
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
01344
42.7%
2601
19.1%
:393
 
12.5%
-262
 
8.3%
1244
 
7.8%
5140
 
4.5%
+131
 
4.2%
415
 
0.5%
68
 
0.3%
33
 
0.1%
Other values (3)3
 
0.1%
Latin
ValueCountFrequency (%)
T131
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII3275
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
01344
41.0%
2601
18.4%
:393
 
12.0%
-262
 
8.0%
1244
 
7.5%
5140
 
4.3%
T131
 
4.0%
+131
 
4.0%
415
 
0.5%
68
 
0.2%
Other values (4)6
 
0.2%

runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct43
Distinct (%)38.4%
Missing19
Missing (%)14.5%
Infinite0
Infinite (%)0.0%
Mean30.3125
Minimum1
Maximum73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:21:21.910138image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.55
Q117
median29.5
Q345
95-th percentile60.45
Maximum73
Range72
Interquartile range (IQR)28

Descriptive statistics

Standard deviation17.68953029
Coefficient of variation (CV)0.5835721334
Kurtosis-1.040934551
Mean30.3125
Median Absolute Deviation (MAD)15.5
Skewness0.1711345582
Sum3395
Variance312.919482
MonotonicityNot monotonic
2022-05-09T21:21:22.007650image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
4521
16.0%
77
 
5.3%
206
 
4.6%
305
 
3.8%
385
 
3.8%
175
 
3.8%
215
 
3.8%
194
 
3.1%
503
 
2.3%
83
 
2.3%
Other values (33)48
36.6%
(Missing)19
 
14.5%
ValueCountFrequency (%)
11
 
0.8%
43
2.3%
52
 
1.5%
62
 
1.5%
77
5.3%
83
2.3%
92
 
1.5%
103
2.3%
111
 
0.8%
141
 
0.8%
ValueCountFrequency (%)
731
 
0.8%
641
 
0.8%
621
 
0.8%
613
2.3%
601
 
0.8%
581
 
0.8%
572
1.5%
551
 
0.8%
531
 
0.8%
503
2.3%

image
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct52
Distinct (%)100.0%
Missing79
Missing (%)60.3%
Memory size1.1 KiB
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726553.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726553.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/292/732462.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/292/732462.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726629.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726629.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/291/729312.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/291/729312.jpg'}
 
1
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/727232.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/727232.jpg'}
 
1
Other values (47)
47 

Length

Max length176
Median length176
Mean length176
Min length176

Characters and Unicode

Total characters9152
Distinct characters38
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)100.0%

Sample

1st row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/353/883109.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/353/883109.jpg'}
2nd row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/393/983022.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/393/983022.jpg'}
3rd row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/393/983023.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/393/983023.jpg'}
4th row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/295/738238.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/295/738238.jpg'}
5th row{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/285/714188.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/285/714188.jpg'}

Common Values

ValueCountFrequency (%)
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726553.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726553.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/292/732462.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/292/732462.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726629.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726629.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/291/729312.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/291/729312.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/727232.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/727232.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/291/728783.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/291/728783.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/291/727777.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/291/727777.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/293/732804.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/293/732804.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726584.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726584.jpg'}1
 
0.8%
{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726632.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726632.jpg'}1
 
0.8%
Other values (42)42
32.1%
(Missing)79
60.3%

Length

2022-05-09T21:21:22.117866image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
medium52
25.0%
original52
25.0%
https://static.tvmaze.com/uploads/images/original_untouched/290/726879.jpg1
 
0.5%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726610.jpg1
 
0.5%
https://static.tvmaze.com/uploads/images/original_untouched/290/726884.jpg1
 
0.5%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726884.jpg1
 
0.5%
https://static.tvmaze.com/uploads/images/original_untouched/290/726883.jpg1
 
0.5%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726883.jpg1
 
0.5%
https://static.tvmaze.com/uploads/images/original_untouched/290/726882.jpg1
 
0.5%
https://static.tvmaze.com/uploads/images/medium_landscape/290/726882.jpg1
 
0.5%
Other values (96)96
46.2%

Most occurring characters

ValueCountFrequency (%)
/728
 
8.0%
a624
 
6.8%
t572
 
6.2%
m520
 
5.7%
i520
 
5.7%
s468
 
5.1%
e416
 
4.5%
'416
 
4.5%
o364
 
4.0%
p364
 
4.0%
Other values (28)4160
45.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6136
67.0%
Other Punctuation1716
 
18.8%
Decimal Number936
 
10.2%
Space Separator156
 
1.7%
Connector Punctuation104
 
1.1%
Close Punctuation52
 
0.6%
Open Punctuation52
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a624
 
10.2%
t572
 
9.3%
m520
 
8.5%
i520
 
8.5%
s468
 
7.6%
e416
 
6.8%
o364
 
5.9%
p364
 
5.9%
g312
 
5.1%
c312
 
5.1%
Other values (9)1664
27.1%
Decimal Number
ValueCountFrequency (%)
2218
23.3%
7128
13.7%
9116
12.4%
090
9.6%
690
9.6%
586
 
9.2%
376
 
8.1%
868
 
7.3%
136
 
3.8%
428
 
3.0%
Other Punctuation
ValueCountFrequency (%)
/728
42.4%
'416
24.2%
.312
18.2%
:208
 
12.1%
,52
 
3.0%
Space Separator
ValueCountFrequency (%)
156
100.0%
Connector Punctuation
ValueCountFrequency (%)
_104
100.0%
Close Punctuation
ValueCountFrequency (%)
}52
100.0%
Open Punctuation
ValueCountFrequency (%)
{52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin6136
67.0%
Common3016
33.0%

Most frequent character per script

Common
ValueCountFrequency (%)
/728
24.1%
'416
13.8%
.312
10.3%
2218
 
7.2%
:208
 
6.9%
156
 
5.2%
7128
 
4.2%
9116
 
3.8%
_104
 
3.4%
090
 
3.0%
Other values (9)540
17.9%
Latin
ValueCountFrequency (%)
a624
 
10.2%
t572
 
9.3%
m520
 
8.5%
i520
 
8.5%
s468
 
7.6%
e416
 
6.8%
o364
 
5.9%
p364
 
5.9%
g312
 
5.1%
c312
 
5.1%
Other values (9)1664
27.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII9152
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/728
 
8.0%
a624
 
6.8%
t572
 
6.2%
m520
 
5.7%
i520
 
5.7%
s468
 
5.1%
e416
 
4.5%
'416
 
4.5%
o364
 
4.0%
p364
 
4.0%
Other values (28)4160
45.5%

summary
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct44
Distinct (%)33.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
nan
88 
<p>Randi stubbornly claims that she did not throw Jeanette's Christmas decorations. Bitten doubts the Christmas mood, while August gets barracks fever.</p>
 
1
<p>Wade decides to take a vacation after breaking up with his boyfriend Eric. His mother Vivian also arrives in their vacation house as she too is brokenhearted. As they try to rearrange and clean up to ‘'move on," Wade stumbles upon a letter written by a Jose Manuel for a certain Luis. His curiosity opens up to a lot of possibilities - who is this Jose Manuel? Is this a fateful coincidence and the start of something magical?</p>
 
1
<p>Somebody believes that "Sex for Money" is a win-win game. Really?! What does it take for "Daw" to live her net-idol life?</p>
 
1
<p>When Justin tasks Fin with creating an original song to be performed in the film, Fin surprises himself and everyone else when he discovers that his new song is directly connected to one Zach had been writing but was unable to finish before he passed away. Nothing short of a miracle, the story deeply touches Justin and, especially Zach's girlfriend, Amy.</p><p> </p><p> </p>
 
1
Other values (39)
39 

Length

Max length673
Median length3
Mean length57.93129771
Min length3

Characters and Unicode

Total characters7589
Distinct characters76
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)32.8%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan88
67.2%
<p>Randi stubbornly claims that she did not throw Jeanette's Christmas decorations. Bitten doubts the Christmas mood, while August gets barracks fever.</p>1
 
0.8%
<p>Wade decides to take a vacation after breaking up with his boyfriend Eric. His mother Vivian also arrives in their vacation house as she too is brokenhearted. As they try to rearrange and clean up to ‘'move on," Wade stumbles upon a letter written by a Jose Manuel for a certain Luis. His curiosity opens up to a lot of possibilities - who is this Jose Manuel? Is this a fateful coincidence and the start of something magical?</p>1
 
0.8%
<p>Somebody believes that "Sex for Money" is a win-win game. Really?! What does it take for "Daw" to live her net-idol life?</p>1
 
0.8%
<p>When Justin tasks Fin with creating an original song to be performed in the film, Fin surprises himself and everyone else when he discovers that his new song is directly connected to one Zach had been writing but was unable to finish before he passed away. Nothing short of a miracle, the story deeply touches Justin and, especially Zach's girlfriend, Amy.</p><p> </p><p> </p>1
 
0.8%
<p>Two elderly ladies from St.Petersburg, Russia, who tried to bring a park bench into a trolleybus, immediately hit the headlines and were made into a popular meme after a short video from the shoot had been posted on the Internet. The video turned out to be so absurd and topical that it became a TikTok hit instantaneously and got 100 million views on different social media. After that, it received extensive coverage on the state TV channels, and the main characters of the story became household names all over Russia. The enormous country kept wondering who the women were, why they needed that bench, what was going on, and if that was fake news or not. <br /> </p>1
 
0.8%
<p>Super 7 can be traced back to the magazine born out of owner Brian Flynn's love of collecting Kaiju toys. Since then, it's grown into not only a retailer of collectibles &amp; apparel, but also as a producer of esoteric &amp; imaginative products.</p>1
 
0.8%
<p>Located in the former Fireplace Shanty of Mays Landing New Jersey is a "Museum of Memories" as Justin and Penelope Daniels like to call it. We know it as Farpoint Toys, one of the most beloved toy stores in America.</p>1
 
0.8%
<p>Batcave Comics &amp; Toys owners Mike Holbrook &amp; Amanda Barlow share more than just their namesake with the caped crusader, they're both do-gooders in their own right; such as donating comics to local youth charities while under quarantine.</p>1
 
0.8%
<p>Down in Kokomo...Indiana, Todd &amp; Amber Jordan have built one of the most impressive toy stores you'll ever see. With row upon row of exclusives &amp; rarities, Kokomo Toys &amp; Collectibles is the cornerstone of what's become known as "Geek St."</p>1
 
0.8%
Other values (34)34
 
26.0%

Length

2022-05-09T21:21:22.234426image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan88
 
6.8%
the59
 
4.6%
to36
 
2.8%
a34
 
2.6%
and30
 
2.3%
of26
 
2.0%
in17
 
1.3%
for15
 
1.2%
p14
 
1.1%
is13
 
1.0%
Other values (671)953
74.2%

Most occurring characters

ValueCountFrequency (%)
1138
15.0%
e693
 
9.1%
n557
 
7.3%
a547
 
7.2%
t447
 
5.9%
o417
 
5.5%
s395
 
5.2%
i390
 
5.1%
r354
 
4.7%
h269
 
3.5%
Other values (66)2382
31.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5706
75.2%
Space Separator1154
 
15.2%
Other Punctuation251
 
3.3%
Uppercase Letter230
 
3.0%
Math Symbol224
 
3.0%
Decimal Number13
 
0.2%
Dash Punctuation10
 
0.1%
Initial Punctuation1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e693
12.1%
n557
 
9.8%
a547
 
9.6%
t447
 
7.8%
o417
 
7.3%
s395
 
6.9%
i390
 
6.8%
r354
 
6.2%
h269
 
4.7%
p209
 
3.7%
Other values (19)1428
25.0%
Uppercase Letter
ValueCountFrequency (%)
S25
 
10.9%
T19
 
8.3%
B18
 
7.8%
A17
 
7.4%
D15
 
6.5%
M15
 
6.5%
C15
 
6.5%
J13
 
5.7%
L11
 
4.8%
I11
 
4.8%
Other values (13)71
30.9%
Other Punctuation
ValueCountFrequency (%)
.74
29.5%
/61
24.3%
,52
20.7%
'24
 
9.6%
;11
 
4.4%
"9
 
3.6%
&9
 
3.6%
?8
 
3.2%
!2
 
0.8%
1
 
0.4%
Decimal Number
ValueCountFrequency (%)
15
38.5%
02
 
15.4%
92
 
15.4%
21
 
7.7%
51
 
7.7%
71
 
7.7%
41
 
7.7%
Space Separator
ValueCountFrequency (%)
1138
98.6%
 16
 
1.4%
Math Symbol
ValueCountFrequency (%)
<112
50.0%
>112
50.0%
Dash Punctuation
ValueCountFrequency (%)
-8
80.0%
2
 
20.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5936
78.2%
Common1653
 
21.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e693
11.7%
n557
 
9.4%
a547
 
9.2%
t447
 
7.5%
o417
 
7.0%
s395
 
6.7%
i390
 
6.6%
r354
 
6.0%
h269
 
4.5%
p209
 
3.5%
Other values (42)1658
27.9%
Common
ValueCountFrequency (%)
1138
68.8%
<112
 
6.8%
>112
 
6.8%
.74
 
4.5%
/61
 
3.7%
,52
 
3.1%
'24
 
1.5%
 16
 
1.0%
;11
 
0.7%
"9
 
0.5%
Other values (14)44
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII7564
99.7%
None21
 
0.3%
Punctuation4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1138
15.0%
e693
 
9.2%
n557
 
7.4%
a547
 
7.2%
t447
 
5.9%
o417
 
5.5%
s395
 
5.2%
i390
 
5.2%
r354
 
4.7%
h269
 
3.6%
Other values (59)2357
31.2%
None
ValueCountFrequency (%)
 16
76.2%
ö2
 
9.5%
å2
 
9.5%
ä1
 
4.8%
Punctuation
ValueCountFrequency (%)
2
50.0%
1
25.0%
1
25.0%

_embedded_show_id
Real number (ℝ≥0)

HIGH CORRELATION

Distinct76
Distinct (%)58.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48703.38931
Minimum7847
Maximum61909
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:21:22.350501image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum7847
5-th percentile14055
Q146028.5
median52412
Q354665
95-th percentile60949
Maximum61909
Range54062
Interquartile range (IQR)8636.5

Descriptive statistics

Standard deviation11919.26721
Coefficient of variation (CV)0.2447317811
Kurtosis2.987220971
Mean48703.38931
Median Absolute Deviation (MAD)4124
Skewness-1.816805347
Sum6380144
Variance142068930.9
MonotonicityNot monotonic
2022-05-09T21:21:22.470567image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5957913
 
9.9%
429668
 
6.1%
140557
 
5.3%
523726
 
4.6%
609495
 
3.8%
326114
 
3.1%
524514
 
3.1%
570293
 
2.3%
519713
 
2.3%
619093
 
2.3%
Other values (66)75
57.3%
ValueCountFrequency (%)
78471
 
0.8%
140557
5.3%
191111
 
0.8%
207341
 
0.8%
306061
 
0.8%
326114
3.1%
354201
 
0.8%
381711
 
0.8%
381991
 
0.8%
414902
 
1.5%
ValueCountFrequency (%)
619093
 
2.3%
609495
 
3.8%
608091
 
0.8%
596761
 
0.8%
5957913
9.9%
583671
 
0.8%
573851
 
0.8%
570293
 
2.3%
564331
 
0.8%
554031
 
0.8%

_embedded_show_url
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct76
Distinct (%)58.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
https://www.tvmaze.com/shows/59579/filly-funtasia
13 
https://www.tvmaze.com/shows/42966/bridgerton
 
8
https://www.tvmaze.com/shows/14055/letterkenny
 
7
https://www.tvmaze.com/shows/52372/ida-og-martin-pa-notholmen
 
6
https://www.tvmaze.com/shows/60949/a-toy-store-near-you
 
5
Other values (71)
92 

Length

Max length68
Median length62
Mean length50.11450382
Min length39

Characters and Unicode

Total characters6565
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)43.5%

Sample

1st rowhttps://www.tvmaze.com/shows/7847/po-sezonu-videodajdzest-seasonvar
2nd rowhttps://www.tvmaze.com/shows/38199/fiksiki
3rd rowhttps://www.tvmaze.com/shows/48288/roast-battle-labelcom
4th rowhttps://www.tvmaze.com/shows/49280/psih
5th rowhttps://www.tvmaze.com/shows/52520/muzskaa-tema

Common Values

ValueCountFrequency (%)
https://www.tvmaze.com/shows/59579/filly-funtasia13
 
9.9%
https://www.tvmaze.com/shows/42966/bridgerton8
 
6.1%
https://www.tvmaze.com/shows/14055/letterkenny7
 
5.3%
https://www.tvmaze.com/shows/52372/ida-og-martin-pa-notholmen6
 
4.6%
https://www.tvmaze.com/shows/60949/a-toy-store-near-you5
 
3.8%
https://www.tvmaze.com/shows/32611/var-tid-ar-nu4
 
3.1%
https://www.tvmaze.com/shows/52451/the-burning-river4
 
3.1%
https://www.tvmaze.com/shows/57029/bablo3
 
2.3%
https://www.tvmaze.com/shows/51971/wish-you3
 
2.3%
https://www.tvmaze.com/shows/61909/mighty-little-bheem-kite-festival3
 
2.3%
Other values (66)75
57.3%

Length

2022-05-09T21:21:22.602190image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.tvmaze.com/shows/59579/filly-funtasia13
 
9.9%
https://www.tvmaze.com/shows/42966/bridgerton8
 
6.1%
https://www.tvmaze.com/shows/14055/letterkenny7
 
5.3%
https://www.tvmaze.com/shows/52372/ida-og-martin-pa-notholmen6
 
4.6%
https://www.tvmaze.com/shows/60949/a-toy-store-near-you5
 
3.8%
https://www.tvmaze.com/shows/32611/var-tid-ar-nu4
 
3.1%
https://www.tvmaze.com/shows/52451/the-burning-river4
 
3.1%
https://www.tvmaze.com/shows/57029/bablo3
 
2.3%
https://www.tvmaze.com/shows/51971/wish-you3
 
2.3%
https://www.tvmaze.com/shows/61909/mighty-little-bheem-kite-festival3
 
2.3%
Other values (66)75
57.3%

Most occurring characters

ValueCountFrequency (%)
/655
 
10.0%
w539
 
8.2%
t539
 
8.2%
s476
 
7.3%
o389
 
5.9%
m325
 
5.0%
e319
 
4.9%
h313
 
4.8%
a281
 
4.3%
.262
 
4.0%
Other values (30)2467
37.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4648
70.8%
Other Punctuation1048
 
16.0%
Decimal Number656
 
10.0%
Dash Punctuation213
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w539
11.6%
t539
11.6%
s476
10.2%
o389
 
8.4%
m325
 
7.0%
e319
 
6.9%
h313
 
6.7%
a281
 
6.0%
p159
 
3.4%
c157
 
3.4%
Other values (16)1151
24.8%
Decimal Number
ValueCountFrequency (%)
5135
20.6%
281
12.3%
980
12.2%
474
11.3%
168
10.4%
658
8.8%
754
 
8.2%
047
 
7.2%
331
 
4.7%
828
 
4.3%
Other Punctuation
ValueCountFrequency (%)
/655
62.5%
.262
 
25.0%
:131
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
-213
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4648
70.8%
Common1917
29.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
w539
11.6%
t539
11.6%
s476
10.2%
o389
 
8.4%
m325
 
7.0%
e319
 
6.9%
h313
 
6.7%
a281
 
6.0%
p159
 
3.4%
c157
 
3.4%
Other values (16)1151
24.8%
Common
ValueCountFrequency (%)
/655
34.2%
.262
 
13.7%
-213
 
11.1%
5135
 
7.0%
:131
 
6.8%
281
 
4.2%
980
 
4.2%
474
 
3.9%
168
 
3.5%
658
 
3.0%
Other values (4)160
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII6565
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/655
 
10.0%
w539
 
8.2%
t539
 
8.2%
s476
 
7.3%
o389
 
5.9%
m325
 
5.0%
e319
 
4.9%
h313
 
4.8%
a281
 
4.3%
.262
 
4.0%
Other values (30)2467
37.6%

_embedded_show_name
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct76
Distinct (%)58.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Filly Funtasia
13 
Bridgerton
 
8
Letterkenny
 
7
Ida og Martin på Notholmen
 
6
A Toy Store Near You
 
5
Other values (71)
92 

Length

Max length34
Median length23
Mean length15.19847328
Min length4

Characters and Unicode

Total characters1991
Distinct characters91
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)43.5%

Sample

1st rowПо сезону. Видеодайджест Seasonvar
2nd rowФиксики
3rd rowRoast Battle Labelcom
4th rowПсих
5th rowМужская тема

Common Values

ValueCountFrequency (%)
Filly Funtasia13
 
9.9%
Bridgerton8
 
6.1%
Letterkenny7
 
5.3%
Ida og Martin på Notholmen6
 
4.6%
A Toy Store Near You5
 
3.8%
Vår tid är nu4
 
3.1%
The Burning River4
 
3.1%
Bablo3
 
2.3%
Wish You3
 
2.3%
Mighty Little Bheem: Kite Festival3
 
2.3%
Other values (66)75
57.3%

Length

2022-05-09T21:21:22.734256image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the15
 
4.4%
funtasia13
 
3.8%
filly13
 
3.8%
you10
 
2.9%
bridgerton8
 
2.3%
a8
 
2.3%
letterkenny7
 
2.0%
ida6
 
1.8%
og6
 
1.8%
martin6
 
1.8%
Other values (166)250
73.1%

Most occurring characters

ValueCountFrequency (%)
211
 
10.6%
e178
 
8.9%
n121
 
6.1%
t121
 
6.1%
i120
 
6.0%
o118
 
5.9%
a112
 
5.6%
r95
 
4.8%
l79
 
4.0%
u55
 
2.8%
Other values (81)781
39.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1455
73.1%
Uppercase Letter311
 
15.6%
Space Separator211
 
10.6%
Other Punctuation10
 
0.5%
Dash Punctuation2
 
0.1%
Decimal Number2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e178
12.2%
n121
 
8.3%
t121
 
8.3%
i120
 
8.2%
o118
 
8.1%
a112
 
7.7%
r95
 
6.5%
l79
 
5.4%
u55
 
3.8%
s55
 
3.8%
Other values (36)401
27.6%
Uppercase Letter
ValueCountFrequency (%)
F35
 
11.3%
L30
 
9.6%
M25
 
8.0%
T22
 
7.1%
B20
 
6.4%
S20
 
6.4%
N15
 
4.8%
R14
 
4.5%
Y12
 
3.9%
A11
 
3.5%
Other values (29)107
34.4%
Other Punctuation
ValueCountFrequency (%)
:8
80.0%
.1
 
10.0%
,1
 
10.0%
Space Separator
ValueCountFrequency (%)
211
100.0%
Dash Punctuation
ValueCountFrequency (%)
-2
100.0%
Decimal Number
ValueCountFrequency (%)
22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1683
84.5%
Common225
 
11.3%
Cyrillic83
 
4.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e178
 
10.6%
n121
 
7.2%
t121
 
7.2%
i120
 
7.1%
o118
 
7.0%
a112
 
6.7%
r95
 
5.6%
l79
 
4.7%
u55
 
3.3%
s55
 
3.3%
Other values (44)629
37.4%
Cyrillic
ValueCountFrequency (%)
а10
 
12.0%
и8
 
9.6%
е7
 
8.4%
к7
 
8.4%
с7
 
8.4%
д6
 
7.2%
о4
 
4.8%
П3
 
3.6%
р3
 
3.6%
т2
 
2.4%
Other values (21)26
31.3%
Common
ValueCountFrequency (%)
211
93.8%
:8
 
3.6%
-2
 
0.9%
22
 
0.9%
.1
 
0.4%
,1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII1892
95.0%
Cyrillic83
 
4.2%
None16
 
0.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
211
 
11.2%
e178
 
9.4%
n121
 
6.4%
t121
 
6.4%
i120
 
6.3%
o118
 
6.2%
a112
 
5.9%
r95
 
5.0%
l79
 
4.2%
u55
 
2.9%
Other values (47)682
36.0%
None
ValueCountFrequency (%)
å10
62.5%
ä5
31.2%
é1
 
6.2%
Cyrillic
ValueCountFrequency (%)
а10
 
12.0%
и8
 
9.6%
е7
 
8.4%
к7
 
8.4%
с7
 
8.4%
д6
 
7.2%
о4
 
4.8%
П3
 
3.6%
р3
 
3.6%
т2
 
2.4%
Other values (21)26
31.3%

_embedded_show_type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct8
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Scripted
75 
Animation
25 
Documentary
21 
Talk Show
 
3
Game Show
 
2
Other values (3)
 
5

Length

Max length11
Median length8
Mean length8.664122137
Min length6

Characters and Unicode

Total characters1135
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st rowTalk Show
2nd rowAnimation
3rd rowGame Show
4th rowScripted
5th rowTalk Show

Common Values

ValueCountFrequency (%)
Scripted75
57.3%
Animation25
 
19.1%
Documentary21
 
16.0%
Talk Show3
 
2.3%
Game Show2
 
1.5%
Variety2
 
1.5%
Reality2
 
1.5%
Sports1
 
0.8%

Length

2022-05-09T21:21:22.828072image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:21:22.938207image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
scripted75
55.1%
animation25
 
18.4%
documentary21
 
15.4%
show5
 
3.7%
talk3
 
2.2%
game2
 
1.5%
variety2
 
1.5%
reality2
 
1.5%
sports1
 
0.7%

Most occurring characters

ValueCountFrequency (%)
i129
11.4%
t126
11.1%
e102
9.0%
r99
8.7%
c96
8.5%
S81
 
7.1%
p76
 
6.7%
d75
 
6.6%
n71
 
6.3%
a55
 
4.8%
Other values (16)225
19.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter994
87.6%
Uppercase Letter136
 
12.0%
Space Separator5
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i129
13.0%
t126
12.7%
e102
10.3%
r99
10.0%
c96
9.7%
p76
7.6%
d75
7.5%
n71
7.1%
a55
5.5%
o52
5.2%
Other values (8)113
11.4%
Uppercase Letter
ValueCountFrequency (%)
S81
59.6%
A25
 
18.4%
D21
 
15.4%
T3
 
2.2%
G2
 
1.5%
V2
 
1.5%
R2
 
1.5%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1130
99.6%
Common5
 
0.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
i129
11.4%
t126
11.2%
e102
9.0%
r99
8.8%
c96
8.5%
S81
 
7.2%
p76
 
6.7%
d75
 
6.6%
n71
 
6.3%
a55
 
4.9%
Other values (15)220
19.5%
Common
ValueCountFrequency (%)
5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1135
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i129
11.4%
t126
11.1%
e102
9.0%
r99
8.7%
c96
8.5%
S81
 
7.1%
p76
 
6.7%
d75
 
6.6%
n71
 
6.3%
a55
 
4.8%
Other values (16)225
19.8%

_embedded_show_language
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct16
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
English
45 
Chinese
27 
Norwegian
13 
Russian
10 
Korean
10 
Other values (11)
26 

Length

Max length10
Median length7
Mean length6.908396947
Min length3

Characters and Unicode

Total characters905
Distinct characters31
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)3.1%

Sample

1st rowRussian
2nd rowRussian
3rd rowRussian
4th rowRussian
5th rowRussian

Common Values

ValueCountFrequency (%)
English45
34.4%
Chinese27
20.6%
Norwegian13
 
9.9%
Russian10
 
7.6%
Korean10
 
7.6%
Swedish4
 
3.1%
Thai4
 
3.1%
nan4
 
3.1%
Spanish3
 
2.3%
Tagalog3
 
2.3%
Other values (6)8
 
6.1%

Length

2022-05-09T21:21:23.048570image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english45
34.4%
chinese27
20.6%
norwegian13
 
9.9%
russian10
 
7.6%
korean10
 
7.6%
swedish4
 
3.1%
thai4
 
3.1%
nan4
 
3.1%
spanish3
 
2.3%
tagalog3
 
2.3%
Other values (6)8
 
6.1%

Most occurring characters

ValueCountFrequency (%)
n121
13.4%
i109
12.0%
s102
11.3%
e87
9.6%
h85
9.4%
g66
7.3%
a54
 
6.0%
l49
 
5.4%
E45
 
5.0%
o29
 
3.2%
Other values (21)158
17.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter778
86.0%
Uppercase Letter127
 
14.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n121
15.6%
i109
14.0%
s102
13.1%
e87
11.2%
h85
10.9%
g66
8.5%
a54
6.9%
l49
6.3%
o29
 
3.7%
r26
 
3.3%
Other values (8)50
6.4%
Uppercase Letter
ValueCountFrequency (%)
E45
35.4%
C27
21.3%
N13
 
10.2%
R10
 
7.9%
K10
 
7.9%
S7
 
5.5%
T7
 
5.5%
D2
 
1.6%
P2
 
1.6%
M1
 
0.8%
Other values (3)3
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Latin905
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n121
13.4%
i109
12.0%
s102
11.3%
e87
9.6%
h85
9.4%
g66
7.3%
a54
 
6.0%
l49
 
5.4%
E45
 
5.0%
o29
 
3.2%
Other values (21)158
17.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII905
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n121
13.4%
i109
12.0%
s102
11.3%
e87
9.6%
h85
9.4%
g66
7.3%
a54
 
6.0%
l49
 
5.4%
E45
 
5.0%
o29
 
3.2%
Other values (21)158
17.5%

_embedded_show_genres
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct35
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
[]
33 
['Drama', 'Romance']
19 
['Comedy']
13 
['Comedy', 'Children']
['Drama']
Other values (30)
53 

Length

Max length46
Median length41
Mean length16.29007634
Min length2

Characters and Unicode

Total characters2134
Distinct characters35
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)15.3%

Sample

1st row[]
2nd row[]
3rd row['Comedy']
4th row['Drama', 'Thriller']
5th row[]

Common Values

ValueCountFrequency (%)
[]33
25.2%
['Drama', 'Romance']19
14.5%
['Comedy']13
 
9.9%
['Comedy', 'Children']7
 
5.3%
['Drama']6
 
4.6%
['Nature']6
 
4.6%
['Drama', 'Romance', 'History']4
 
3.1%
['Drama', 'Comedy', 'Romance']4
 
3.1%
['Drama', 'Action', 'Thriller']4
 
3.1%
['Drama', 'Music', 'Romance']3
 
2.3%
Other values (25)32
24.4%

Length

2022-05-09T21:21:23.143432image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
drama54
22.8%
romance35
14.8%
comedy35
14.8%
33
13.9%
action10
 
4.2%
history8
 
3.4%
thriller7
 
3.0%
fantasy7
 
3.0%
crime7
 
3.0%
children7
 
3.0%
Other values (13)34
14.3%

Most occurring characters

ValueCountFrequency (%)
'408
19.1%
a174
 
8.2%
m140
 
6.6%
[131
 
6.1%
]131
 
6.1%
e116
 
5.4%
r113
 
5.3%
,106
 
5.0%
106
 
5.0%
o95
 
4.5%
Other values (25)614
28.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1046
49.0%
Other Punctuation514
24.1%
Uppercase Letter206
 
9.7%
Open Punctuation131
 
6.1%
Close Punctuation131
 
6.1%
Space Separator106
 
5.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a174
16.6%
m140
13.4%
e116
11.1%
r113
10.8%
o95
9.1%
n72
6.9%
y55
 
5.3%
i52
 
5.0%
c49
 
4.7%
d48
 
4.6%
Other values (7)132
12.6%
Uppercase Letter
ValueCountFrequency (%)
D55
26.7%
C49
23.8%
R35
17.0%
A20
 
9.7%
F12
 
5.8%
H9
 
4.4%
T8
 
3.9%
N6
 
2.9%
M5
 
2.4%
S4
 
1.9%
Other values (3)3
 
1.5%
Other Punctuation
ValueCountFrequency (%)
'408
79.4%
,106
 
20.6%
Open Punctuation
ValueCountFrequency (%)
[131
100.0%
Close Punctuation
ValueCountFrequency (%)
]131
100.0%
Space Separator
ValueCountFrequency (%)
106
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1252
58.7%
Common882
41.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a174
13.9%
m140
11.2%
e116
 
9.3%
r113
 
9.0%
o95
 
7.6%
n72
 
5.8%
y55
 
4.4%
D55
 
4.4%
i52
 
4.2%
c49
 
3.9%
Other values (20)331
26.4%
Common
ValueCountFrequency (%)
'408
46.3%
[131
 
14.9%
]131
 
14.9%
,106
 
12.0%
106
 
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2134
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
'408
19.1%
a174
 
8.2%
m140
 
6.6%
[131
 
6.1%
]131
 
6.1%
e116
 
5.4%
r113
 
5.3%
,106
 
5.0%
106
 
5.0%
o95
 
4.5%
Other values (25)614
28.8%

_embedded_show_status
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct3
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Running
72 
Ended
38 
To Be Determined
21 

Length

Max length16
Median length7
Mean length7.86259542
Min length5

Characters and Unicode

Total characters1030
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRunning
2nd rowRunning
3rd rowRunning
4th rowEnded
5th rowEnded

Common Values

ValueCountFrequency (%)
Running72
55.0%
Ended38
29.0%
To Be Determined21
 
16.0%

Length

2022-05-09T21:21:23.237182image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:21:23.331131image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
running72
41.6%
ended38
22.0%
to21
 
12.1%
be21
 
12.1%
determined21
 
12.1%

Most occurring characters

ValueCountFrequency (%)
n275
26.7%
e122
11.8%
d97
 
9.4%
i93
 
9.0%
R72
 
7.0%
u72
 
7.0%
g72
 
7.0%
42
 
4.1%
E38
 
3.7%
T21
 
2.0%
Other values (6)126
12.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter815
79.1%
Uppercase Letter173
 
16.8%
Space Separator42
 
4.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n275
33.7%
e122
15.0%
d97
 
11.9%
i93
 
11.4%
u72
 
8.8%
g72
 
8.8%
o21
 
2.6%
t21
 
2.6%
r21
 
2.6%
m21
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
R72
41.6%
E38
22.0%
T21
 
12.1%
B21
 
12.1%
D21
 
12.1%
Space Separator
ValueCountFrequency (%)
42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin988
95.9%
Common42
 
4.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
n275
27.8%
e122
12.3%
d97
 
9.8%
i93
 
9.4%
R72
 
7.3%
u72
 
7.3%
g72
 
7.3%
E38
 
3.8%
T21
 
2.1%
o21
 
2.1%
Other values (5)105
 
10.6%
Common
ValueCountFrequency (%)
42
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1030
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n275
26.7%
e122
11.8%
d97
 
9.4%
i93
 
9.0%
R72
 
7.0%
u72
 
7.0%
g72
 
7.0%
42
 
4.1%
E38
 
3.7%
T21
 
2.0%
Other values (6)126
12.2%

_embedded_show_runtime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct21
Distinct (%)30.0%
Missing61
Missing (%)46.6%
Infinite0
Infinite (%)0.0%
Mean30.7
Minimum1
Maximum62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:21:23.412444image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q115
median38
Q345
95-th percentile50
Maximum62
Range61
Interquartile range (IQR)30

Descriptive statistics

Standard deviation16.44873459
Coefficient of variation (CV)0.5357894003
Kurtosis-1.288706947
Mean30.7
Median Absolute Deviation (MAD)11
Skewness-0.2607124701
Sum2149
Variance270.5608696
MonotonicityNot monotonic
2022-05-09T21:21:23.500258image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
4519
 
14.5%
108
 
6.1%
407
 
5.3%
305
 
3.8%
205
 
3.8%
504
 
3.1%
383
 
2.3%
253
 
2.3%
52
 
1.5%
42
 
1.5%
Other values (11)12
 
9.2%
(Missing)61
46.6%
ValueCountFrequency (%)
11
 
0.8%
42
 
1.5%
52
 
1.5%
61
 
0.8%
71
 
0.8%
91
 
0.8%
108
6.1%
141
 
0.8%
152
 
1.5%
171
 
0.8%
ValueCountFrequency (%)
621
 
0.8%
601
 
0.8%
504
 
3.1%
481
 
0.8%
4519
14.5%
407
 
5.3%
383
 
2.3%
305
 
3.8%
253
 
2.3%
231
 
0.8%

_embedded_show_averageRuntime
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct34
Distinct (%)29.8%
Missing17
Missing (%)13.0%
Infinite0
Infinite (%)0.0%
Mean30.57894737
Minimum1
Maximum62
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:21:23.601075image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q114.25
median26.5
Q345
95-th percentile62
Maximum62
Range61
Interquartile range (IQR)30.75

Descriptive statistics

Standard deviation17.98863689
Coefficient of variation (CV)0.5882686764
Kurtosis-1.156131007
Mean30.57894737
Median Absolute Deviation (MAD)16.5
Skewness0.2119633983
Sum3486
Variance323.5910573
MonotonicityNot monotonic
2022-05-09T21:21:23.732116image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
4519
14.5%
249
 
6.9%
629
 
6.9%
207
 
5.3%
387
 
5.3%
305
 
3.8%
75
 
3.8%
584
 
3.1%
104
 
3.1%
503
 
2.3%
Other values (24)42
32.1%
(Missing)17
13.0%
ValueCountFrequency (%)
11
 
0.8%
42
 
1.5%
52
 
1.5%
62
 
1.5%
75
3.8%
83
2.3%
92
 
1.5%
104
3.1%
113
2.3%
123
2.3%
ValueCountFrequency (%)
629
6.9%
601
 
0.8%
584
 
3.1%
541
 
0.8%
503
 
2.3%
481
 
0.8%
461
 
0.8%
4519
14.5%
422
 
1.5%
401
 
0.8%

_embedded_show_premiered
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct58
Distinct (%)44.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2020-12-25
19 
2019-03-11
13 
2020-12-04
2016-02-07
 
7
2020-12-11
 
6
Other values (53)
77 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters1310
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)31.3%

Sample

1st row2015-02-13
2nd row2010-12-13
3rd row2019-12-24
4th row2020-11-05
5th row2020-12-17

Common Values

ValueCountFrequency (%)
2020-12-2519
 
14.5%
2019-03-1113
 
9.9%
2020-12-049
 
6.9%
2016-02-077
 
5.3%
2020-12-116
 
4.6%
2020-05-295
 
3.8%
2017-10-024
 
3.1%
2020-12-214
 
3.1%
2020-12-244
 
3.1%
2019-01-173
 
2.3%
Other values (48)57
43.5%

Length

2022-05-09T21:21:23.989154image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-12-2519
 
14.5%
2019-03-1113
 
9.9%
2020-12-049
 
6.9%
2016-02-077
 
5.3%
2020-12-116
 
4.6%
2020-05-295
 
3.8%
2017-10-024
 
3.1%
2020-12-214
 
3.1%
2020-12-244
 
3.1%
2019-01-173
 
2.3%
Other values (48)57
43.5%

Most occurring characters

ValueCountFrequency (%)
2339
25.9%
0319
24.4%
-262
20.0%
1220
16.8%
939
 
3.0%
534
 
2.6%
426
 
2.0%
724
 
1.8%
321
 
1.6%
617
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1048
80.0%
Dash Punctuation262
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2339
32.3%
0319
30.4%
1220
21.0%
939
 
3.7%
534
 
3.2%
426
 
2.5%
724
 
2.3%
321
 
2.0%
617
 
1.6%
89
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
-262
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1310
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2339
25.9%
0319
24.4%
-262
20.0%
1220
16.8%
939
 
3.0%
534
 
2.6%
426
 
2.0%
724
 
1.8%
321
 
1.6%
617
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII1310
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2339
25.9%
0319
24.4%
-262
20.0%
1220
16.8%
939
 
3.0%
534
 
2.6%
426
 
2.0%
724
 
1.8%
321
 
1.6%
617
 
1.3%

_embedded_show_ended
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct22
Distinct (%)16.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
nan
93 
2020-12-25
10 
2021-01-07
 
2
2021-01-04
 
2
2021-01-02
 
2
Other values (17)
22 

Length

Max length10
Median length3
Mean length5.030534351
Min length3

Characters and Unicode

Total characters659
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)9.2%

Sample

1st rownan
2nd rownan
3rd rownan
4th row2020-12-24
5th row2020-12-25

Common Values

ValueCountFrequency (%)
nan93
71.0%
2020-12-2510
 
7.6%
2021-01-072
 
1.5%
2021-01-042
 
1.5%
2021-01-022
 
1.5%
2021-01-282
 
1.5%
2020-12-312
 
1.5%
2021-03-122
 
1.5%
2021-01-142
 
1.5%
2021-01-292
 
1.5%
Other values (12)12
 
9.2%

Length

2022-05-09T21:21:24.078718image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan93
71.0%
2020-12-2510
 
7.6%
2021-01-072
 
1.5%
2021-01-042
 
1.5%
2021-01-022
 
1.5%
2021-01-282
 
1.5%
2020-12-312
 
1.5%
2021-03-122
 
1.5%
2021-01-142
 
1.5%
2021-01-292
 
1.5%
Other values (12)12
 
9.2%

Most occurring characters

ValueCountFrequency (%)
n186
28.2%
2117
17.8%
a93
14.1%
088
13.4%
-76
11.5%
165
 
9.9%
513
 
2.0%
45
 
0.8%
84
 
0.6%
34
 
0.6%
Other values (3)8
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number304
46.1%
Lowercase Letter279
42.3%
Dash Punctuation76
 
11.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2117
38.5%
088
28.9%
165
21.4%
513
 
4.3%
45
 
1.6%
84
 
1.3%
34
 
1.3%
93
 
1.0%
63
 
1.0%
72
 
0.7%
Lowercase Letter
ValueCountFrequency (%)
n186
66.7%
a93
33.3%
Dash Punctuation
ValueCountFrequency (%)
-76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common380
57.7%
Latin279
42.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2117
30.8%
088
23.2%
-76
20.0%
165
17.1%
513
 
3.4%
45
 
1.3%
84
 
1.1%
34
 
1.1%
93
 
0.8%
63
 
0.8%
Latin
ValueCountFrequency (%)
n186
66.7%
a93
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII659
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n186
28.2%
2117
17.8%
a93
14.1%
088
13.4%
-76
11.5%
165
 
9.9%
513
 
2.0%
45
 
0.8%
84
 
0.6%
34
 
0.6%
Other values (3)8
 
1.2%

_embedded_show_officialSite
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct66
Distinct (%)50.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
nan
27 
https://www.netflix.com/title/80232398
https://www.crave.ca/tv-shows/letterkenny
 
7
https://tv.nrk.no/serie/ida-og-martin-paa-notholmen
 
6
https://www.amazon.com/gp/video/detail/B0891S22PR/
 
5
Other values (61)
78 

Length

Max length250
Median length78
Mean length41.47328244
Min length3

Characters and Unicode

Total characters5433
Distinct characters75
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)38.9%

Sample

1st rowhttp://seasonvar.ru/serial-11488-Po_sezonu_Videodajdzhest_Seasonvar.html
2nd rowhttp://www.fixiki.ru
3rd rowhttps://www.youtube.com/playlist?list=PLmkbS48df311cZnmhlV-5q5vY0icLXdl3
4th rowhttps://more.tv/psih
5th rowhttps://www.ivi.ru/watch/muzhskaya-tema

Common Values

ValueCountFrequency (%)
nan27
20.6%
https://www.netflix.com/title/802323988
 
6.1%
https://www.crave.ca/tv-shows/letterkenny7
 
5.3%
https://tv.nrk.no/serie/ida-og-martin-paa-notholmen6
 
4.6%
https://www.amazon.com/gp/video/detail/B0891S22PR/5
 
3.8%
https://v.youku.com/v_show/id_XNDk1MzY2NzgwNA==.html?spm=a2h0c.8166622.PhoneSokuProgram_1.dtitle&s=aaed627feea749d7a99d4
 
3.1%
https://www.svtplay.se/var-tid-ar-nu4
 
3.1%
https://www.viki.com/tv/37486c-wish-you3
 
2.3%
https://tv.nrk.no/serie/bablo3
 
2.3%
https://www.netflix.com/title/812737283
 
2.3%
Other values (56)61
46.6%

Length

2022-05-09T21:21:24.188100image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan27
20.6%
https://www.netflix.com/title/802323988
 
6.1%
https://www.crave.ca/tv-shows/letterkenny7
 
5.3%
https://tv.nrk.no/serie/ida-og-martin-paa-notholmen6
 
4.6%
https://www.amazon.com/gp/video/detail/b0891s22pr5
 
3.8%
https://v.youku.com/v_show/id_xndk1mzy2nzgwna==.html?spm=a2h0c.8166622.phonesokuprogram_1.dtitle&s=aaed627feea749d7a99d4
 
3.1%
https://www.svtplay.se/var-tid-ar-nu4
 
3.1%
https://www.viki.com/tv/37486c-wish-you3
 
2.3%
https://tv.nrk.no/serie/bablo3
 
2.3%
https://www.netflix.com/title/812737283
 
2.3%
Other values (56)61
46.6%

Most occurring characters

ValueCountFrequency (%)
/421
 
7.7%
t413
 
7.6%
w244
 
4.5%
s237
 
4.4%
.225
 
4.1%
e224
 
4.1%
a223
 
4.1%
o215
 
4.0%
i210
 
3.9%
h185
 
3.4%
Other values (65)2836
52.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3491
64.3%
Other Punctuation830
 
15.3%
Decimal Number660
 
12.1%
Uppercase Letter288
 
5.3%
Dash Punctuation91
 
1.7%
Math Symbol39
 
0.7%
Connector Punctuation34
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t413
 
11.8%
w244
 
7.0%
s237
 
6.8%
e224
 
6.4%
a223
 
6.4%
o215
 
6.2%
i210
 
6.0%
h185
 
5.3%
n185
 
5.3%
p170
 
4.9%
Other values (16)1185
33.9%
Uppercase Letter
ValueCountFrequency (%)
P30
 
10.4%
A20
 
6.9%
S20
 
6.9%
N19
 
6.6%
B19
 
6.6%
E16
 
5.6%
L15
 
5.2%
D14
 
4.9%
C14
 
4.9%
R14
 
4.9%
Other values (16)107
37.2%
Decimal Number
ValueCountFrequency (%)
189
13.5%
288
13.3%
872
10.9%
070
10.6%
969
10.5%
361
9.2%
657
8.6%
756
8.5%
454
8.2%
544
6.7%
Other Punctuation
ValueCountFrequency (%)
/421
50.7%
.225
27.1%
:122
 
14.7%
%33
 
4.0%
?18
 
2.2%
&9
 
1.1%
#1
 
0.1%
!1
 
0.1%
Math Symbol
ValueCountFrequency (%)
=36
92.3%
+2
 
5.1%
~1
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
-91
100.0%
Connector Punctuation
ValueCountFrequency (%)
_34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3779
69.6%
Common1654
30.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t413
 
10.9%
w244
 
6.5%
s237
 
6.3%
e224
 
5.9%
a223
 
5.9%
o215
 
5.7%
i210
 
5.6%
h185
 
4.9%
n185
 
4.9%
p170
 
4.5%
Other values (42)1473
39.0%
Common
ValueCountFrequency (%)
/421
25.5%
.225
13.6%
:122
 
7.4%
-91
 
5.5%
189
 
5.4%
288
 
5.3%
872
 
4.4%
070
 
4.2%
969
 
4.2%
361
 
3.7%
Other values (13)346
20.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII5433
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/421
 
7.7%
t413
 
7.6%
w244
 
4.5%
s237
 
4.4%
.225
 
4.1%
e224
 
4.1%
a223
 
4.1%
o215
 
4.0%
i210
 
3.9%
h185
 
3.4%
Other values (65)2836
52.2%

_embedded_show_weight
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct45
Distinct (%)34.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.5648855
Minimum0
Maximum98
Zeros5
Zeros (%)3.8%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:21:24.343679image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q18
median29
Q364.5
95-th percentile98
Maximum98
Range98
Interquartile range (IQR)56.5

Descriptive statistics

Standard deviation31.70030314
Coefficient of variation (CV)0.821999151
Kurtosis-0.8936897417
Mean38.5648855
Median Absolute Deviation (MAD)21
Skewness0.6244353662
Sum5052
Variance1004.909219
MonotonicityNot monotonic
2022-05-09T21:21:24.469426image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
815
 
11.5%
249
 
6.9%
988
 
6.1%
38
 
6.1%
977
 
5.3%
186
 
4.6%
05
 
3.8%
175
 
3.8%
444
 
3.1%
154
 
3.1%
Other values (35)60
45.8%
ValueCountFrequency (%)
05
 
3.8%
12
 
1.5%
38
6.1%
51
 
0.8%
62
 
1.5%
71
 
0.8%
815
11.5%
101
 
0.8%
141
 
0.8%
154
 
3.1%
ValueCountFrequency (%)
988
6.1%
977
5.3%
961
 
0.8%
881
 
0.8%
831
 
0.8%
792
 
1.5%
781
 
0.8%
751
 
0.8%
711
 
0.8%
694
3.1%

_embedded_show_dvdCountry
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
nan
130 
{'name': 'Russian Federation', 'code': 'RU', 'timezone': 'Asia/Kamchatka'}
 
1

Length

Max length74
Median length3
Mean length3.541984733
Min length3

Characters and Unicode

Total characters464
Distinct characters27
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan

Common Values

ValueCountFrequency (%)
nan130
99.2%
{'name': 'Russian Federation', 'code': 'RU', 'timezone': 'Asia/Kamchatka'}1
 
0.8%

Length

2022-05-09T21:21:24.576503image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-05-09T21:21:24.699085image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
nan130
94.9%
name1
 
0.7%
russian1
 
0.7%
federation1
 
0.7%
code1
 
0.7%
ru1
 
0.7%
timezone1
 
0.7%
asia/kamchatka1
 
0.7%

Most occurring characters

ValueCountFrequency (%)
n264
56.9%
a137
29.5%
'12
 
2.6%
e6
 
1.3%
6
 
1.3%
i4
 
0.9%
m3
 
0.6%
:3
 
0.6%
o3
 
0.6%
s3
 
0.6%
Other values (17)23
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter432
93.1%
Other Punctuation18
 
3.9%
Space Separator6
 
1.3%
Uppercase Letter6
 
1.3%
Open Punctuation1
 
0.2%
Close Punctuation1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n264
61.1%
a137
31.7%
e6
 
1.4%
i4
 
0.9%
m3
 
0.7%
o3
 
0.7%
s3
 
0.7%
t3
 
0.7%
c2
 
0.5%
d2
 
0.5%
Other values (5)5
 
1.2%
Uppercase Letter
ValueCountFrequency (%)
R2
33.3%
F1
16.7%
U1
16.7%
A1
16.7%
K1
16.7%
Other Punctuation
ValueCountFrequency (%)
'12
66.7%
:3
 
16.7%
,2
 
11.1%
/1
 
5.6%
Space Separator
ValueCountFrequency (%)
6
100.0%
Open Punctuation
ValueCountFrequency (%)
{1
100.0%
Close Punctuation
ValueCountFrequency (%)
}1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin438
94.4%
Common26
 
5.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
n264
60.3%
a137
31.3%
e6
 
1.4%
i4
 
0.9%
m3
 
0.7%
o3
 
0.7%
s3
 
0.7%
t3
 
0.7%
c2
 
0.5%
d2
 
0.5%
Other values (10)11
 
2.5%
Common
ValueCountFrequency (%)
'12
46.2%
6
23.1%
:3
 
11.5%
,2
 
7.7%
{1
 
3.8%
/1
 
3.8%
}1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII464
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n264
56.9%
a137
29.5%
'12
 
2.6%
e6
 
1.3%
6
 
1.3%
i4
 
0.9%
m3
 
0.6%
:3
 
0.6%
o3
 
0.6%
s3
 
0.6%
Other values (17)23
 
5.0%

_embedded_show_summary
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct69
Distinct (%)52.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
nan
20 
<p>Based on Julia Quinn's best-selling series of novels, <b>Bridgerton</b> is set in the sexy, lavish and competitive world of Regency London high society. From the glittering ballrooms of Mayfair to the aristocratic palaces of Park Lane and beyond, the series unveils a seductive, sumptuous world replete with intricate rules and dramatic power struggles, where no one is truly ever on steady ground. At the heart of the show is the powerful Bridgerton family. Comprised of eight close-knit siblings, this funny, witty, daring and clever group must navigate the upper ten thousand's marriage mart in search of romance, adventure and love.</p>
 
8
<p>Wayne is a good-ol' country boy in <b>Letterkenny</b>, Ontario trying to protect his homegrown way of life on the farm, against a world that is constantly evolving around him. The residents of Letterkenny belong to one of three groups: Hicks, Skids, and Hockey Players. The three groups are constantly feuding with each other over seemingly trivial matters; often ending with someone getting their ass kicked.</p>
 
7
<p>Ida and Martin pause city life and move to a small islet on the Romsdal coast. At Notholmen, they will explore an easier way of living.</p>
 
6
<p>Throughout the world, there are hundreds of independently-owned toy stores, each one as unique and endearing as the people that own them. For the loyal customers that flock to them, they're more than simply an outlet to obtain new treasures; they're a community.</p>
 
5
Other values (64)
85 

Length

Max length1360
Median length705
Mean length356.3587786
Min length3

Characters and Unicode

Total characters46683
Distinct characters97
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)38.2%

Sample

1st row<p>Weekly videodaydzhest on site seasonvar.ru and creative team viruseproject.tv. In ten minutes, we talk about the most important events of the past week: look down on the set is not yet published projects, sharing the secrets of private life actors consider the prospects for the development of genres and discuss news TV industry! In videodaydzheste you will find only reliable information from Russian and foreign publications, as well as take part in choosing the best show of the month! Our weekly news videodaydzhest will suit every viewer, so gather good company with family and friends, as well as stock up on popcorn - these ten minutes you shock, delight and inform the latest news about your favorite TV projects!</p>
2nd rownan
3rd row<p>A bold humorous show in which comedians fight for 50,000 rubles! Six comedians will take to the stage to "fry" each other. The top two will go to the final, and only one will take the money with them!</p>
4th row<p>Oleg is a metropolitan psychotherapist. Clients of the central district of Moscow line up to him. Only lately Oleg doesn't like them, he tolerates them. Midlife crisis, life with mom at 40, loss of self-esteem, drug addiction, irritability and growing aggression. None of the clients are aware of his problems. From the outside, he seems successful, happily married, wealthy. Nobody knows the truth.</p><p> </p><p>A year ago, his wife went missing. She has been gone for 384 days.</p>
5th row<p><b>Мужская тема</b> is a symbiosis of talk shows and modern podcasts, where male celebrities answer questions that concern people in the XXI century. Bright representatives of show business, theater, pop, cinema, sports, as well as Internet stars meet in the barbershop. Here, on male territory, they can openly discuss a variety of topics, sometimes seriously, and sometimes with humor. This is a chance to see the idol in a confidential communication without notes, compare his opinion with your own and hear what men really talk about when there is not a single girl around.</p>

Common Values

ValueCountFrequency (%)
nan20
 
15.3%
<p>Based on Julia Quinn's best-selling series of novels, <b>Bridgerton</b> is set in the sexy, lavish and competitive world of Regency London high society. From the glittering ballrooms of Mayfair to the aristocratic palaces of Park Lane and beyond, the series unveils a seductive, sumptuous world replete with intricate rules and dramatic power struggles, where no one is truly ever on steady ground. At the heart of the show is the powerful Bridgerton family. Comprised of eight close-knit siblings, this funny, witty, daring and clever group must navigate the upper ten thousand's marriage mart in search of romance, adventure and love.</p>8
 
6.1%
<p>Wayne is a good-ol' country boy in <b>Letterkenny</b>, Ontario trying to protect his homegrown way of life on the farm, against a world that is constantly evolving around him. The residents of Letterkenny belong to one of three groups: Hicks, Skids, and Hockey Players. The three groups are constantly feuding with each other over seemingly trivial matters; often ending with someone getting their ass kicked.</p>7
 
5.3%
<p>Ida and Martin pause city life and move to a small islet on the Romsdal coast. At Notholmen, they will explore an easier way of living.</p>6
 
4.6%
<p>Throughout the world, there are hundreds of independently-owned toy stores, each one as unique and endearing as the people that own them. For the loyal customers that flock to them, they're more than simply an outlet to obtain new treasures; they're a community.</p>5
 
3.8%
<p>Two boggling mysteries have occured in a small town in Xinan. A female police captain joins hands with a young detective to conduct an investigation. Although a clear motive can be seen, the two discover a series of unknown secrets.</p><p>One case involves a late-night ride hailed through an online platform that goes terribly wrong. As more and more clues resurface, the cases in the hands of the police hands become complicated and entangled. In a desperate attempt to find the real culprit, events closely link the past, present and future of the small town.</p>4
 
3.1%
<p>The Löwander family operate one of the most prestigious restaurants in Stockholm, exploring what becomes of the establishment as a new era dawns.</p>4
 
3.1%
<p>A free-spirited singer whose love of music has him performing on the streets, Kang In Soo's life revolves completely around music. Supported by his friends, In Soo hopes to someday turn his love of music into a full-time career, but doing so isn't easy. Refusing to give up on his dreams, In Soo continues busking, day in and day out, while his best friend, Choi Min Sung, records his performances and uploads them on YouTube. Little does either of them know that In Soo's performances have caught the attention of someone who could change the young musician's life forever.</p><p>A keyboardist working at a major record company, Yoon Sang Yi is always on the lookout for new talent. After stumbling upon In Soo's videos, Sang Yi has become one of the singer's biggest fans. Convinced In Soo could make it big, he recommends the young artist join his company's rookie discovery project. Seeing this opportunity in this invitation, In Soo accepts the offer and soon moves into the company residence with Sang Yi.</p><p>As the two live and work together, their relationship grows and slowly, new feelings begin to blossom. Unfortunately, as their feelings grow, so do the obstacles that stand in their way. Will In Soo and Sang Yi be able to find a way to overcome the trials before them or will their love fade before ever having a chance to fully bloom?</p>3
 
2.3%
<p>With winter behind them, Bheem and his townspeople usher in a sunny new season in all their favorite ways during the Makar Sankranti festival.</p>3
 
2.3%
<p>Welcome to <b>Bablo</b>, the world's best library!</p>3
 
2.3%
Other values (59)68
51.9%

Length

2022-05-09T21:21:24.852013image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the484
 
6.2%
of274
 
3.5%
and251
 
3.2%
a213
 
2.7%
to207
 
2.6%
in163
 
2.1%
is96
 
1.2%
with75
 
1.0%
on71
 
0.9%
his71
 
0.9%
Other values (1807)5935
75.7%

Most occurring characters

ValueCountFrequency (%)
7699
16.5%
e4435
 
9.5%
t3032
 
6.5%
o2841
 
6.1%
n2795
 
6.0%
a2717
 
5.8%
i2527
 
5.4%
s2280
 
4.9%
r2191
 
4.7%
h1833
 
3.9%
Other values (87)14333
30.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter35501
76.0%
Space Separator7710
 
16.5%
Other Punctuation1290
 
2.8%
Uppercase Letter1249
 
2.7%
Math Symbol733
 
1.6%
Dash Punctuation95
 
0.2%
Decimal Number64
 
0.1%
Format14
 
< 0.1%
Open Punctuation13
 
< 0.1%
Close Punctuation13
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e4435
12.5%
t3032
 
8.5%
o2841
 
8.0%
n2795
 
7.9%
a2717
 
7.7%
i2527
 
7.1%
s2280
 
6.4%
r2191
 
6.2%
h1833
 
5.2%
l1496
 
4.2%
Other values (28)9354
26.3%
Uppercase Letter
ValueCountFrequency (%)
S129
 
10.3%
T105
 
8.4%
A93
 
7.4%
L89
 
7.1%
W84
 
6.7%
M62
 
5.0%
I61
 
4.9%
B60
 
4.8%
Y57
 
4.6%
X57
 
4.6%
Other values (18)452
36.2%
Other Punctuation
ValueCountFrequency (%)
,491
38.1%
.390
30.2%
/192
 
14.9%
'108
 
8.4%
"37
 
2.9%
!21
 
1.6%
;18
 
1.4%
:18
 
1.4%
?14
 
1.1%
&1
 
0.1%
Decimal Number
ValueCountFrequency (%)
020
31.2%
113
20.3%
28
 
12.5%
36
 
9.4%
95
 
7.8%
45
 
7.8%
73
 
4.7%
83
 
4.7%
51
 
1.6%
Math Symbol
ValueCountFrequency (%)
<366
49.9%
>366
49.9%
+1
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
-86
90.5%
7
 
7.4%
2
 
2.1%
Space Separator
ValueCountFrequency (%)
7699
99.9%
 11
 
0.1%
Format
ValueCountFrequency (%)
14
100.0%
Open Punctuation
ValueCountFrequency (%)
(13
100.0%
Close Punctuation
ValueCountFrequency (%)
)13
100.0%
Currency Symbol
ValueCountFrequency (%)
$1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin36739
78.7%
Common9933
 
21.3%
Cyrillic11
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e4435
12.1%
t3032
 
8.3%
o2841
 
7.7%
n2795
 
7.6%
a2717
 
7.4%
i2527
 
6.9%
s2280
 
6.2%
r2191
 
6.0%
h1833
 
5.0%
l1496
 
4.1%
Other values (46)10592
28.8%
Common
ValueCountFrequency (%)
7699
77.5%
,491
 
4.9%
.390
 
3.9%
<366
 
3.7%
>366
 
3.7%
/192
 
1.9%
'108
 
1.1%
-86
 
0.9%
"37
 
0.4%
!21
 
0.2%
Other values (21)177
 
1.8%
Cyrillic
ValueCountFrequency (%)
а2
18.2%
м1
9.1%
е1
9.1%
т1
9.1%
я1
9.1%
к1
9.1%
с1
9.1%
у1
9.1%
М1
9.1%
ж1
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII46628
99.9%
Punctuation23
 
< 0.1%
None21
 
< 0.1%
Cyrillic11
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7699
16.5%
e4435
 
9.5%
t3032
 
6.5%
o2841
 
6.1%
n2795
 
6.0%
a2717
 
5.8%
i2527
 
5.4%
s2280
 
4.9%
r2191
 
4.7%
h1833
 
3.9%
Other values (69)14278
30.6%
Punctuation
ValueCountFrequency (%)
14
60.9%
7
30.4%
2
 
8.7%
None
ValueCountFrequency (%)
 11
52.4%
ö4
 
19.0%
Í3
 
14.3%
ä2
 
9.5%
á1
 
4.8%
Cyrillic
ValueCountFrequency (%)
а2
18.2%
м1
9.1%
е1
9.1%
т1
9.1%
я1
9.1%
к1
9.1%
с1
9.1%
у1
9.1%
М1
9.1%
ж1
9.1%

_embedded_show_updated
Real number (ℝ≥0)

HIGH CORRELATION

Distinct76
Distinct (%)58.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1634129873
Minimum1604587145
Maximum1652080636
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2022-05-09T21:21:24.992939image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1604587145
5-th percentile1609008712
Q11619414456
median1640013095
Q31647562926
95-th percentile1651898238
Maximum1652080636
Range47493491
Interquartile range (IQR)28148470

Descriptive statistics

Standard deviation15743584.67
Coefficient of variation (CV)0.009634230992
Kurtosis-1.324887299
Mean1634129873
Median Absolute Deviation (MAD)10267010
Skewness-0.5246003755
Sum2.140710134 × 1011
Variance2.478604582 × 1014
MonotonicityNot monotonic
2022-05-09T21:21:25.150586image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
164001309513
 
9.9%
16502801058
 
6.1%
16475629267
 
5.3%
16090087126
 
4.6%
16470250265
 
3.8%
16208994464
 
3.1%
16080333034
 
3.1%
16342924673
 
2.3%
16410470763
 
2.3%
16520392983
 
2.3%
Other values (66)75
57.3%
ValueCountFrequency (%)
16045871451
 
0.8%
16080333034
3.1%
16090087126
4.6%
16091813541
 
0.8%
16095364481
 
0.8%
16096488851
 
0.8%
16096516762
 
1.5%
16097998962
 
1.5%
16099236481
 
0.8%
16103080041
 
0.8%
ValueCountFrequency (%)
16520806361
 
0.8%
16520392983
2.3%
16520354301
 
0.8%
16519333631
 
0.8%
16519332091
 
0.8%
16518632662
1.5%
16511816551
 
0.8%
16505526741
 
0.8%
16503092011
 
0.8%
16502868781
 
0.8%

_links_self_href
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct131
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
https://api.tvmaze.com/episodes/1977902
 
1
https://api.tvmaze.com/episodes/2001669
 
1
https://api.tvmaze.com/episodes/2001667
 
1
https://api.tvmaze.com/episodes/2001666
 
1
https://api.tvmaze.com/episodes/2001665
 
1
Other values (126)
126 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters5109
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique131 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/1977902
2nd rowhttps://api.tvmaze.com/episodes/2015818
3rd rowhttps://api.tvmaze.com/episodes/1964000
4th rowhttps://api.tvmaze.com/episodes/1995405
5th rowhttps://api.tvmaze.com/episodes/2007760

Common Values

ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19779021
 
0.8%
https://api.tvmaze.com/episodes/20016691
 
0.8%
https://api.tvmaze.com/episodes/20016671
 
0.8%
https://api.tvmaze.com/episodes/20016661
 
0.8%
https://api.tvmaze.com/episodes/20016651
 
0.8%
https://api.tvmaze.com/episodes/20000731
 
0.8%
https://api.tvmaze.com/episodes/20000721
 
0.8%
https://api.tvmaze.com/episodes/19975381
 
0.8%
https://api.tvmaze.com/episodes/19975371
 
0.8%
https://api.tvmaze.com/episodes/19884051
 
0.8%
Other values (121)121
92.4%

Length

2022-05-09T21:21:25.317229image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/19779021
 
0.8%
https://api.tvmaze.com/episodes/23122251
 
0.8%
https://api.tvmaze.com/episodes/19640001
 
0.8%
https://api.tvmaze.com/episodes/19954051
 
0.8%
https://api.tvmaze.com/episodes/20077601
 
0.8%
https://api.tvmaze.com/episodes/19857891
 
0.8%
https://api.tvmaze.com/episodes/20396221
 
0.8%
https://api.tvmaze.com/episodes/20396231
 
0.8%
https://api.tvmaze.com/episodes/23244271
 
0.8%
https://api.tvmaze.com/episodes/23244281
 
0.8%
Other values (121)121
92.4%

Most occurring characters

ValueCountFrequency (%)
/524
 
10.3%
p393
 
7.7%
s393
 
7.7%
e393
 
7.7%
t393
 
7.7%
o262
 
5.1%
a262
 
5.1%
i262
 
5.1%
.262
 
5.1%
m262
 
5.1%
Other values (16)1703
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3275
64.1%
Other Punctuation917
 
17.9%
Decimal Number917
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p393
12.0%
s393
12.0%
e393
12.0%
t393
12.0%
o262
8.0%
a262
8.0%
i262
8.0%
m262
8.0%
h131
 
4.0%
d131
 
4.0%
Other values (3)393
12.0%
Decimal Number
ValueCountFrequency (%)
2142
15.5%
9141
15.4%
0124
13.5%
1111
12.1%
378
8.5%
674
8.1%
871
7.7%
461
6.7%
760
6.5%
555
 
6.0%
Other Punctuation
ValueCountFrequency (%)
/524
57.1%
.262
28.6%
:131
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin3275
64.1%
Common1834
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/524
28.6%
.262
14.3%
2142
 
7.7%
9141
 
7.7%
:131
 
7.1%
0124
 
6.8%
1111
 
6.1%
378
 
4.3%
674
 
4.0%
871
 
3.9%
Other values (3)176
 
9.6%
Latin
ValueCountFrequency (%)
p393
12.0%
s393
12.0%
e393
12.0%
t393
12.0%
o262
8.0%
a262
8.0%
i262
8.0%
m262
8.0%
h131
 
4.0%
d131
 
4.0%
Other values (3)393
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII5109
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/524
 
10.3%
p393
 
7.7%
s393
 
7.7%
e393
 
7.7%
t393
 
7.7%
o262
 
5.1%
a262
 
5.1%
i262
 
5.1%
.262
 
5.1%
m262
 
5.1%
Other values (16)1703
33.3%

Interactions

2022-05-09T21:21:16.495508image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:20:46.781949image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:20:55.185285image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:20:58.407928image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:01.757863image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:05.490766image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:09.855728image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:11.694507image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:14.007237image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:17.577131image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:20:48.387154image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:20:56.694040image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:20:59.801721image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:03.906582image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:06.908143image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:10.492627image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:12.726586image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:15.191455image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:17.681681image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:20:48.889215image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:20:56.844131image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:20:59.959148image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:04.055374image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:07.306121image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:10.587500image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:12.833407image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:15.287448image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:17.777975image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:20:49.514873image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:20:56.970054image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:00.109893image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:04.175144image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:07.608294image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:10.779551image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:12.929830image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:15.379344image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:17.889308image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:20:49.985944image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:20:57.090973image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:00.245894image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:04.290022image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:07.923233image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:10.869259image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:13.022077image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:15.473617image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:18.519055image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:20:51.201361image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:20:57.943473image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:01.069412image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:05.056695image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:08.707014image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:11.326802image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:13.610652image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:16.116655image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:18.621098image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:20:51.744496image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:20:58.059146image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:01.312786image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:05.174021image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:08.959968image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:11.419082image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:13.712237image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:16.207520image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:18.718637image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:20:53.240072image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:20:58.183164image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:01.427465image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:05.274232image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:09.244738image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:11.517677image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:13.810204image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:16.306193image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:18.814838image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:20:54.093856image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:20:58.288411image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:01.608158image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:05.375414image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:09.548126image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:11.607642image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:13.906454image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2022-05-09T21:21:16.397095image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Correlations

2022-05-09T21:21:25.395839image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-05-09T21:21:25.584762image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-05-09T21:21:25.748080image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-05-09T21:21:25.947861image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2022-05-09T21:21:26.369046image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-05-09T21:21:19.136074image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
A simple visualization of nullity by column.
2022-05-09T21:21:19.829693image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-05-09T21:21:20.030862image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-05-09T21:21:20.177613image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummary_embedded_show_id_embedded_show_url_embedded_show_name_embedded_show_type_embedded_show_language_embedded_show_genres_embedded_show_status_embedded_show_runtime_embedded_show_averageRuntime_embedded_show_premiered_embedded_show_ended_embedded_show_officialSite_embedded_show_weight_embedded_show_dvdCountry_embedded_show_summary_embedded_show_updated_links_self_href
01968115https://www.tvmaze.com/episodes/1968115/po-sezonu-videodajdzest-seasonvar-6x52-vypusk-306Выпуск 3066.052.0regular2020-12-25nan2020-12-25T00:00:00+00:007.0Nonenan7847https://www.tvmaze.com/shows/7847/po-sezonu-videodajdzest-seasonvarПо сезону. Видеодайджест SeasonvarTalk ShowRussian[]Running9.09.02015-02-13nanhttp://seasonvar.ru/serial-11488-Po_sezonu_Videodajdzhest_Seasonvar.html28.0nan<p>Weekly videodaydzhest on site seasonvar.ru and creative team viruseproject.tv. In ten minutes, we talk about the most important events of the past week: look down on the set is not yet published projects, sharing the secrets of private life actors consider the prospects for the development of genres and discuss news TV industry! In videodaydzheste you will find only reliable information from Russian and foreign publications, as well as take part in choosing the best show of the month! Our weekly news videodaydzhest will suit every viewer, so gather good company with family and friends, as well as stock up on popcorn - these ten minutes you shock, delight and inform the latest news about your favorite TV projects!</p>1.651182e+09https://api.tvmaze.com/episodes/1977902
12121269https://www.tvmaze.com/episodes/2121269/fiksiki-4x18-sankiСанки4.018.0regular2020-12-25nan2020-12-25T00:00:00+00:006.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/353/883109.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/353/883109.jpg'}nan38199https://www.tvmaze.com/shows/38199/fiksikiФиксикиAnimationRussian[]Running6.06.02010-12-13nanhttp://www.fixiki.ru1.0nannan1.631301e+09https://api.tvmaze.com/episodes/2015818
21984017https://www.tvmaze.com/episodes/1984017/roast-battle-labelcom-1x15-15-dana-milohin#15 - Даня Милохин1.015.0regular2020-12-25nan2020-12-25T00:00:00+00:0053.0Nonenan48288https://www.tvmaze.com/shows/48288/roast-battle-labelcomRoast Battle LabelcomGame ShowRussian['Comedy']Running50.054.02019-12-24nanhttps://www.youtube.com/playlist?list=PLmkbS48df311cZnmhlV-5q5vY0icLXdl323.0nan<p>A bold humorous show in which comedians fight for 50,000 rubles! Six comedians will take to the stage to "fry" each other. The top two will go to the final, and only one will take the money with them!</p>1.645055e+09https://api.tvmaze.com/episodes/1964000
31991483https://www.tvmaze.com/episodes/1991483/psih-s01-special-film-o-filmeФильм о фильме1.0NaNinsignificant_special2020-12-2512:002020-12-25T00:00:00+00:0029.0Nonenan49280https://www.tvmaze.com/shows/49280/psihПсихScriptedRussian['Drama', 'Thriller']Ended62.062.02020-11-052020-12-24https://more.tv/psih29.0nan<p>Oleg is a metropolitan psychotherapist. Clients of the central district of Moscow line up to him. Only lately Oleg doesn't like them, he tolerates them. Midlife crisis, life with mom at 40, loss of self-esteem, drug addiction, irritability and growing aggression. None of the clients are aware of his problems. From the outside, he seems successful, happily married, wealthy. Nobody knows the truth.</p><p> </p><p>A year ago, his wife went missing. She has been gone for 384 days.</p>1.619195e+09https://api.tvmaze.com/episodes/1995405
41988016https://www.tvmaze.com/episodes/1988016/muzskaa-tema-1x05-seria-5Серия 51.05.0regular2020-12-2512:002020-12-25T00:00:00+00:0030.0Nonenan52520https://www.tvmaze.com/shows/52520/muzskaa-temaМужская темаTalk ShowRussian[]Ended30.030.02020-12-172020-12-25https://www.ivi.ru/watch/muzhskaya-tema3.0nan<p><b>Мужская тема</b> is a symbiosis of talk shows and modern podcasts, where male celebrities answer questions that concern people in the XXI century. Bright representatives of show business, theater, pop, cinema, sports, as well as Internet stars meet in the barbershop. Here, on male territory, they can openly discuss a variety of topics, sometimes seriously, and sometimes with humor. This is a chance to see the idol in a confidential communication without notes, compare his opinion with your own and hear what men really talk about when there is not a single girl around.</p>1.616723e+09https://api.tvmaze.com/episodes/2007760
52062929https://www.tvmaze.com/episodes/2062929/god-of-ten-thousand-realms-1x04-episode-4Episode 41.04.0regular2020-12-2510:002020-12-25T02:00:00+00:007.0Nonenan54541https://www.tvmaze.com/shows/54541/god-of-ten-thousand-realmsGod of Ten Thousand RealmsAnimationChinese['Adventure', 'Anime', 'Fantasy']Running7.07.02020-12-21nanhttps://v.qq.com/detail/m/mzc002007995z4v.html65.0nan<p>At the end of the calendar 2020, the continent of Stern, which has reached the end of civilization due to the exhaustion of magic elements, ushered in the destruction of the continent under the void storm. Ye Xuan, the last god of law in the mainland, unexpectedly awakened in the era of the prosperous magic civilization three thousand years ago and became an ordinary student at the Sith Magic Academy on the border of the Kingdom of Orlando in the northwest of the mainland. In order to save the mainland and prevent the end from coming, Ye Xuan began to explore the mystery of the dark turmoil that led to the depletion of magical elements in the mainland three thousand years ago, to prevent the mainland crisis.</p>1.642689e+09https://api.tvmaze.com/episodes/1985789
62030154https://www.tvmaze.com/episodes/2030154/fox-spirit-matchmaker-9x04-episode-125Episode 1259.04.0regular2020-12-25nan2020-12-25T04:00:00+00:0010.0Nonenan20734https://www.tvmaze.com/shows/20734/fox-spirit-matchmakerFox Spirit MatchmakerAnimationChinese['Comedy', 'Anime', 'Fantasy', 'Romance']Running10.010.02015-06-26nanhttp://www.bilibili.com/bangumi/%E7%8B%90%E5%A6%96%E5%B0%8F%E7%BA%A2%E5%A8%98/64.0nan<p>Buy UCO from childhood grew up in the clan, Ichigo, but their "care" was for him a living Hell. Constant bullying, stealing the Goodies, without which Ycu can not live, and even eternal persecution, from the fair sex turned him into a goner cheapskate who wants to take revenge on his tormentors. But revenge is sweet and the path to it is thorny and to accomplish, UCU need to marry a girl Yes, as soon as possible. But when the heroes just happen? Never! And meeting with the small and the big-eared Fox Susan su su did not just destroy his plans, but starts spinning the wheel of fate that was waiting in the wings for hundreds of years!</p>1.629636e+09https://api.tvmaze.com/episodes/2039622
72324416https://www.tvmaze.com/episodes/2324416/unique-lady-2x07-episode-7Episode 72.07.0regular2020-12-2512:002020-12-25T04:00:00+00:0038.0Nonenan41490https://www.tvmaze.com/shows/41490/unique-ladyUnique LadyScriptedChinese['Drama', 'Comedy', 'Romance']Ended38.042.02019-01-172021-01-07http://www.iqiyi.com/a_19rrhvpyyp.html68.0nan<p>Lin Luo Jing accidentally gets drawn into a game world where she is the daughter of the prime minister and meets all kind of beautiful men with different personalities. Among them are a sword deity, an imperial bodyguard, a playful rich man and an arrogant prince. The system informs her that she can only return to the real world after she finds her true love. While there seems tobe an abundance of good men around Luo Jing, there is one man she can't stand at all: the prince of the barbarian Yuan Kingdom Zhong Wu Mei. But out of all men, she ends up in an arranged marriage with Wu Mei.</p><p>Thus begins their love-hate relationship and her journey to find true love in order to win the game.</p>1.651863e+09https://api.tvmaze.com/episodes/2039623
82324417https://www.tvmaze.com/episodes/2324417/unique-lady-2x08-episode-8Episode 82.08.0regular2020-12-2512:002020-12-25T04:00:00+00:0038.0Nonenan41490https://www.tvmaze.com/shows/41490/unique-ladyUnique LadyScriptedChinese['Drama', 'Comedy', 'Romance']Ended38.042.02019-01-172021-01-07http://www.iqiyi.com/a_19rrhvpyyp.html68.0nan<p>Lin Luo Jing accidentally gets drawn into a game world where she is the daughter of the prime minister and meets all kind of beautiful men with different personalities. Among them are a sword deity, an imperial bodyguard, a playful rich man and an arrogant prince. The system informs her that she can only return to the real world after she finds her true love. While there seems tobe an abundance of good men around Luo Jing, there is one man she can't stand at all: the prince of the barbarian Yuan Kingdom Zhong Wu Mei. But out of all men, she ends up in an arranged marriage with Wu Mei.</p><p>Thus begins their love-hate relationship and her journey to find true love in order to win the game.</p>1.651863e+09https://api.tvmaze.com/episodes/2324427
91972575https://www.tvmaze.com/episodes/1972575/the-wolf-1x33-episode-33Episode 331.033.0regular2020-12-25nan2020-12-25T04:00:00+00:0045.0Nonenan47912https://www.tvmaze.com/shows/47912/the-wolfThe WolfScriptedChinese['Drama', 'Romance', 'History']Ended45.045.02020-11-192021-01-04https://www.iqiyi.com/lib/m_213579814.html39.0nan<p>The story happens at the end of the Tang Dynasty, when Zhu Wen usurps the throne and establishes the Later Liang Dynasty, and he's known as Emperor Taizu. Ma Zhai Xing (Li Qin) is the daughter of an official and as a child, she befriends a young boy (Darren Wang) who lives in the mountain. One day when he saves a wolf, he accidentally falls over the cliff and is rescued by Zhu Wen. The authoritative figure adopts him as a godson and gives him the title Bo Wang. Ten years later, he saves the female lead per chance and finds her courage and intelligence resonant, and she likes that while he's in a position of power, he still has humility and kindness. She encourages him to fight for justice and he begins that journey by helping the people, stopping throne fights, etc. Even when they have conflicts, they will face those frankly. As they overcome obstacles and fight for justice, feelings deepen and they are able to reap their own happiness by each other's side.</p>1.648217e+09https://api.tvmaze.com/episodes/2324428

Last rows

idurlnameseasonnumbertypeairdateairtimeairstampruntimeimagesummary_embedded_show_id_embedded_show_url_embedded_show_name_embedded_show_type_embedded_show_language_embedded_show_genres_embedded_show_status_embedded_show_runtime_embedded_show_averageRuntime_embedded_show_premiered_embedded_show_ended_embedded_show_officialSite_embedded_show_weight_embedded_show_dvdCountry_embedded_show_summary_embedded_show_updated_links_self_href
1211998537https://www.tvmaze.com/episodes/1998537/mermaid-prince-1x23-episode-23Episode 231.023.0regular2020-12-2521:002020-12-25T13:00:00+00:0045.0Nonenan52780https://www.tvmaze.com/shows/52780/mermaid-princeMermaid PrinceScriptedChinese['Comedy', 'Fantasy', 'Romance']Running45.045.02020-11-25nannan24.0nan<p>‎Shen Moo, has no idea what adventures she will face. Beauty, is one of the best observers of Internet resources, but soon, in her head creeps the idea that in the universe there are mermaids. It's hard to believe, but for some reason, she can't get it out of her mind. Soon, she will have to take responsibility to prove their existence, otherwise, the dispute with the professor will turn out to be a real failure for the heroine. Together with the rescue team, they went to help the victims in The Xine Bay. Meet Ahn Xin - an athlete, will turn her reality. Unbelievable, but the guy is perceived as a mermaid. Of course, Mu Xin liked it madly, because she found a key witness and will be able to insist on her own. However, the mermaid man does his best to avoid revealing his real world.‎</p>1.609649e+09https://api.tvmaze.com/episodes/2234297
1222168984https://www.tvmaze.com/episodes/2168984/after-mom-falls-asleep-s04-special-kai-qaKAI Q&A4.0NaNinsignificant_special2020-12-2522:002020-12-25T13:00:00+00:007.0Nonenan57385https://www.tvmaze.com/shows/57385/after-mom-falls-asleepAfter Mom Falls AsleepVarietyKorean['Comedy', 'Food', 'DIY']RunningNaN12.02017-01-26nanhttps://www.pikicast.com/#!/menu=series&series_id=35676244.0nan<p><b>After Mom Falls Asleep</b> is a new variety program by Pikicast that adds an ASMR element to a variety show. Guests must complete missions without waking up "Mom" while she is asleep, which usually involve cooking food and answering questions about themselves.</p>1.650287e+09https://api.tvmaze.com/episodes/2236494
1231990725https://www.tvmaze.com/episodes/1990725/sj-returns-4x87-episode-87Episode 874.087.0regular2020-12-2500:002020-12-25T15:00:00+00:005.0Nonenan52250https://www.tvmaze.com/shows/52250/sj-returnsSJ ReturnsRealityKorean[]Running5.05.02017-10-09nanhttps://tv.naver.com/sjreturns15.0nan<p>This show will follow Super Junior's everyday life.</p>1.613088e+09https://api.tvmaze.com/episodes/1977423
1241972066https://www.tvmaze.com/episodes/1972066/letterkenny-9x01-american-buck-and-doeAmerican Buck and Doe9.01.0regular2020-12-25nan2020-12-25T16:00:00+00:0024.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726554.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726554.jpg'}<p>Post-fight with Dierks, the hicks/skids and hockey players attend an American Buck and Doe.</p>14055https://www.tvmaze.com/shows/14055/letterkennyLetterkennyScriptedEnglish['Comedy']RunningNaN24.02016-02-07nanhttps://www.crave.ca/tv-shows/letterkenny97.0nan<p>Wayne is a good-ol' country boy in <b>Letterkenny</b>, Ontario trying to protect his homegrown way of life on the farm, against a world that is constantly evolving around him. The residents of Letterkenny belong to one of three groups: Hicks, Skids, and Hockey Players. The three groups are constantly feuding with each other over seemingly trivial matters; often ending with someone getting their ass kicked.</p>1.647563e+09https://api.tvmaze.com/episodes/1976649
1251972067https://www.tvmaze.com/episodes/1972067/letterkenny-9x02-kids-with-problemsKids with Problems9.02.0regular2020-12-25nan2020-12-25T16:00:00+00:0030.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726555.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726555.jpg'}<p>Kids with problems are given important life lessons…and hot dogs.</p>14055https://www.tvmaze.com/shows/14055/letterkennyLetterkennyScriptedEnglish['Comedy']RunningNaN24.02016-02-07nanhttps://www.crave.ca/tv-shows/letterkenny97.0nan<p>Wayne is a good-ol' country boy in <b>Letterkenny</b>, Ontario trying to protect his homegrown way of life on the farm, against a world that is constantly evolving around him. The residents of Letterkenny belong to one of three groups: Hicks, Skids, and Hockey Players. The three groups are constantly feuding with each other over seemingly trivial matters; often ending with someone getting their ass kicked.</p>1.647563e+09https://api.tvmaze.com/episodes/2005096
1261972068https://www.tvmaze.com/episodes/1972068/letterkenny-9x03-scorched-earthScorched Earth9.03.0regular2020-12-25nan2020-12-25T16:00:00+00:0021.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726556.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726556.jpg'}<p>Katy takes her scorched earth strategy to Letterkenny. Gail gets some action of her own.</p>14055https://www.tvmaze.com/shows/14055/letterkennyLetterkennyScriptedEnglish['Comedy']RunningNaN24.02016-02-07nanhttps://www.crave.ca/tv-shows/letterkenny97.0nan<p>Wayne is a good-ol' country boy in <b>Letterkenny</b>, Ontario trying to protect his homegrown way of life on the farm, against a world that is constantly evolving around him. The residents of Letterkenny belong to one of three groups: Hicks, Skids, and Hockey Players. The three groups are constantly feuding with each other over seemingly trivial matters; often ending with someone getting their ass kicked.</p>1.647563e+09https://api.tvmaze.com/episodes/2005098
1271972069https://www.tvmaze.com/episodes/1972069/letterkenny-9x04-mitzvahMitzvah9.04.0regular2020-12-25nan2020-12-25T16:00:00+00:0020.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726557.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726557.jpg'}<p>The hockey players learn about Judaism.</p>14055https://www.tvmaze.com/shows/14055/letterkennyLetterkennyScriptedEnglish['Comedy']RunningNaN24.02016-02-07nanhttps://www.crave.ca/tv-shows/letterkenny97.0nan<p>Wayne is a good-ol' country boy in <b>Letterkenny</b>, Ontario trying to protect his homegrown way of life on the farm, against a world that is constantly evolving around him. The residents of Letterkenny belong to one of three groups: Hicks, Skids, and Hockey Players. The three groups are constantly feuding with each other over seemingly trivial matters; often ending with someone getting their ass kicked.</p>1.647563e+09https://api.tvmaze.com/episodes/2005099
1281972070https://www.tvmaze.com/episodes/1972070/letterkenny-9x05-sleepoverSleepover9.05.0regular2020-12-25nan2020-12-25T16:00:00+00:0020.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726558.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726558.jpg'}<p>Sleepover activities only; movies, board games and girl talk.</p>14055https://www.tvmaze.com/shows/14055/letterkennyLetterkennyScriptedEnglish['Comedy']RunningNaN24.02016-02-07nanhttps://www.crave.ca/tv-shows/letterkenny97.0nan<p>Wayne is a good-ol' country boy in <b>Letterkenny</b>, Ontario trying to protect his homegrown way of life on the farm, against a world that is constantly evolving around him. The residents of Letterkenny belong to one of three groups: Hicks, Skids, and Hockey Players. The three groups are constantly feuding with each other over seemingly trivial matters; often ending with someone getting their ass kicked.</p>1.647563e+09https://api.tvmaze.com/episodes/2005100
1291972071https://www.tvmaze.com/episodes/1972071/letterkenny-9x06-breastaurantBreastaurant9.06.0regular2020-12-25nan2020-12-25T16:00:00+00:0020.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726559.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726559.jpg'}<p>A breastaurant opens in Letterkenny.</p>14055https://www.tvmaze.com/shows/14055/letterkennyLetterkennyScriptedEnglish['Comedy']RunningNaN24.02016-02-07nanhttps://www.crave.ca/tv-shows/letterkenny97.0nan<p>Wayne is a good-ol' country boy in <b>Letterkenny</b>, Ontario trying to protect his homegrown way of life on the farm, against a world that is constantly evolving around him. The residents of Letterkenny belong to one of three groups: Hicks, Skids, and Hockey Players. The three groups are constantly feuding with each other over seemingly trivial matters; often ending with someone getting their ass kicked.</p>1.647563e+09https://api.tvmaze.com/episodes/2005101
1301972072https://www.tvmaze.com/episodes/1972072/letterkenny-9x07-ndn-nrgNDN NRG9.07.0regular2020-12-25nan2020-12-25T16:00:00+00:0019.0{'medium': 'https://static.tvmaze.com/uploads/images/medium_landscape/290/726560.jpg', 'original': 'https://static.tvmaze.com/uploads/images/original_untouched/290/726560.jpg'}<p>Tanis starts her own energy drink.</p>14055https://www.tvmaze.com/shows/14055/letterkennyLetterkennyScriptedEnglish['Comedy']RunningNaN24.02016-02-07nanhttps://www.crave.ca/tv-shows/letterkenny97.0nan<p>Wayne is a good-ol' country boy in <b>Letterkenny</b>, Ontario trying to protect his homegrown way of life on the farm, against a world that is constantly evolving around him. The residents of Letterkenny belong to one of three groups: Hicks, Skids, and Hockey Players. The three groups are constantly feuding with each other over seemingly trivial matters; often ending with someone getting their ass kicked.</p>1.647563e+09https://api.tvmaze.com/episodes/2005102